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IBM Certified System Programmer - IBM IMS
IBM Programmer answers
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I’ll be brutally honest. When I set out to write this post, I was going to talk about IBM’s Q Experience — the website where you can run real code on some older IBM quantum computing hardware. I am going to get to that — I promise — but that’s going to have to wait for another time. It turns out that quantum computing is mindbending and — to make matters worse — there are a lot of oversimplifications floating around that make it even harder to understand than it ought to be. Because the IBM system matches up with real hardware, it is has a lot more limitations than a simulator — think of programming a microcontroller with on debugging versus using a software emulator. You can zoom into any level of detail with the emulator but with the bare micro you can toggle a line, use a scope, and hope things don’t go too far wrong.

So before we get to the real quantum hardware, I am going to show you a simulator written by [Craig Gidney]. He wrote it and promptly got a job with Google, who took over the project. Sort of. Even if you don’t like working in a browser, [Craig’s] simulator is easy enough, you don’t need an account, and a bookmark will save your work.

It isn’t the only available simulator, but as [Craig] immodestly (but correctly) points out, his simulator is much better than IBM’s. Starting with the simulator avoids tripping on the hardware limitations. For example, IBM’s devices are not fully connected, like a CPU where only some registers can get to other registers. In addition, real devices have to deal with noise and the quantum states not lasting very long. If your algorithm is too slow, your program will collapse and invalidate your results. These aren’t issues on a simulator. You can find a list of other simulators, but I’m focusing on Quirk.

What Quantum Computing Is

As I mentioned, there is a lot of misinformation about quantum computing (QC) floating around. I think part of it revolves around the word computing. If you are old enough to remember analog computers, QC is much more like that. You build “circuits” to create results. There’s also a lot of difficult math — mostly linear algebra — that I’m going to try to avoid as much as possible. However, if you can dig into the math, it is worth your time to do so. However, just like you can design a resonant circuit without solving differential equations about inductors, I think you can do QC without some of the bigger math by just using results. We’ll see how well that holds up in practice.

QC doesn’t use bits, but qubits. Unsurprisingly a qubit can take a state of 0 or 1. If that was all, then there wouldn’t be much reason to continue the conversation. However, qubits are quantum, so they have two unique properties that QC can exploit. First, a qubit can be some combination of 0 and 1 at the same time. There are famously multiple interpretations of uncertainty in quantum mechanics, but you can think of it as a probability of the qubit being a 0 or a 1. Those probabilities will always add up to 1 and the idea extends to groups of qubits, too. So four qubits have some probability that their state is 0010. If you add up all the probabilities for all the states, you get one. When a qubit is in a combination of states, each with a given probability, that’s called superposition.

You probably know that in quantum mechanics, the state appears to change based on observation. Qubits are the same. While they can be in a superposed state, the instant you measure that state, it becomes either 0 or 1. If you know about Schrödinger’s cat, it is the same principle. In the thought experiment, until you peek, the cat is half dead and half alive just as our qubits can be both 0 and 1.

The other key concept is entanglement. The idea is you can take one qubit and make its state dependent on another qubit’s state even though we don’t know the state of either of them. As a simple example, we can create a qubit that we don’t know the state of, but we know it is opposite of some other qubit that we might also not know about.

Confused? Good. If this makes sense to you, you are probably ahead of where this post is going anyway. Even [Niels Bohr] once said (paraphrasing from Danish), “Anyone who is not shocked by quantum theory has not understood it.”

What Quantum Computing Isn’t

Quantum computing isn’t going to run wordprocessing applications any time soon, if ever. Like I said, it is more like analog computing where you set up a problem and get an answer. Part of that may be the early stage we are in. Part of it is just how it works.

Speaking of how it works, QC is usually probabilistic. So when you search for something, for example, you get the answer to a certain probability. Again, this is like an analog computer. Maybe that probability is 0.99999, but it isn’t going to be 1.0000.

There aren’t many practical quantum algorithms known, and the ones that are known are sometimes difficult to put into practice. For example, if you read hand-waving explanations of QC, you’ll hear that Grover’s algorithm lets you search an unstructured database using fewer queries. A little thinking would probably convince you that this is unlikely. If you are searching a database of animals for “dog” and there’s no way to access it except by index, how could you mysteriously know which index items to skip? You can’t, and neither does Grover’s algorithm.

We’ll talk more about Grover’s in another post, but what the algorithm actually does is match its state to another state that you don’t know in advance. For example, suppose you had a C program that makes a library call that reads like:

int oracle(int x) { if (x==9) return 1; else return 0; }

However, because it is in a library, we don’t know what x has to be to get the 1 return value. If you wrote a program to find out, you might have to call many times. Even if you restricted x to be between 1 and 16, you might have to call sixteen times. You might have to call one time. Grover’s algorithm would call it four times and have a pretty good guess at the answer. This is still not a perfect analogy because the oracle function in QC provides information about which answer is right, so the practicality of it isn’t “unstructured database” as you often hear. A better analogy might be if the oracle looked like this:

int oracle(int x) { if (x==9) return 0; if (x<9) return -1; else return 1; }

Now, even a classic computer could make smarter guesses.

Enough Theory… For Now

We’ll have some more theory later, but your eyes should be good and glazed over by now. I had thought about doing a video about how to use Quirk, but [Craig] did a fine one, so watch that first. When [Craig] compared his simulator to IBM’s he talked about UI design principles he uses and it shows when you use Quirk.

Each of the horizontal lines each represents a qubit and they start in state 0. Time goes from left to right along the qubit and doesn’t go backward, so you read the circuit that way. All of the boxes in the top and bottom gray zones are gates or components that affect the qubits. To the right of the qubits are several ways to visualize the final state of the system. The green boxes show if they are one or zero (or the chances of it, at least). The other two displays will take a little more theory that we’ll talk about next time.

Straight Logic

For now, I want to focus on just the 0 and 1 (technically, |0> and |1>) states. This is just like regular logic, but you can’t use most of the familiar gates you are used to. One that you can use is the NOT gate: the circle with a plus sign in it. Sometimes this also shows up as an X and is known as an X gate. Try it:

As you’d expect, inverting a 0 once creates a 1 and inverting it twice makes a zero. No surprise. There’s also a controlled not (CNOT) gate that is really an exclusive OR gate. That is, if one input is true, the other input inverts. To create one, you just put a dot on any qubit in the same column as an inverter. Try putting a solid dot (from the Probes section) over the second inverter. Note the output and then delete (middle click) the top left inverter. You’ll see the states change where the bottom right inverter only flips the bit if the top qubit is in the 1 state.

Remember that I said there are a lot of oversimplifications that make things hard to understand? This is one of them. The idea that this is a gate with two inputs and one output is only correct in the case that the inputs are 0 or 1. But once we start dealing with qubits in superposed states, this isn’t true anymore. The “input” dot is perfectly capable of modifying the first qubit and — under the right circumstances, you can flip the inverter and the dot and it wouldn’t matter. QC is strange. However, for “computational states” (|0> and |1>) the gate analogy is a fair one. Just don’t forget that it is wrong.

One note about the simulator. If you see NaN on the outputs (short for Not a Number), try using a different browser. I’ve seen some — but not all — versions of some browsers have trouble with the Javascript. That’s not quantum weirdness, a NaN is a normal software bug.

Toffoli Gate

If you are accustomed to normal logic gates, you know that you don’t need all of them. For example, a NAND gate is sufficient to make any other kind of logic gate you want. The NOT and CNOT gates get us part of the way there. The other gate that is easy to implement in QC is a Toffoli gate, sometimes known as a CCNOT gate. You can think of it as a 3-input gate (say, A, B, and C) that has three outputs (X, Y, Z). Two of the outputs are the same as the inputs (that is, X=A, Y=B). The Z output, however, is A AND B XOR C. That’s a bit rough, but you can make whatever gates you want out of that and the NOT/CNOT gate.

To create a Toffoli gate in Quirk, you simply put two dots over an inverter as seen to the right. The two inverters on the left are there to set the inputs to a 1 state. Try it and you’ll see the output is 1 unless you remove either of the inverters. Putting an inverter on the bottom qubit (under the other two inverters) will invert the answer (that’s the XOR C part).

Obviously, configured like this, we have a two-input AND gate. Inverting the inputs gives you an OR gate. Setting the bottom qubit would provide you NAND or NOR. Setting B to 1 would provide A XOR C. Just like the CNOT, this gate can affect its inputs when dealing with quantum states, but we aren’t looking at those yet, so, for now, it is OK to think of the top two qubits along with the bottom left as inputs and the right side of the bottom inverter as an output. Except it isn’t in the general case.

By the way, you’ll see when we use the IBM simulator (which is more like the hardware) there’s no way to build this directly. You have to use many CNOT gates to build one (see below). This is one reason you want to start with Quirk.

Instant Gratification

I think that’s enough for this post, even though we haven’t got to the quantum weirdness yet. However, if you want to jump ahead, select the menu from Quirk and click the Quantum Fourier Transform link. That should keep you dizzy until next time when we talk more theory, get into superposition, and tangle with entanglement.

If you are wondering what’s the point? Hang on to that thought. Right now, we only know about how QC can look like regular logic gates. But that’s just a small part of what you can do with a quantum computer.

Sat, 09 Jul 2022 12:00:00 -0500 Al Williams en-US text/html https://hackaday.com/2018/01/24/quantum-weirdness-in-your-browser/
Killexams : IBM, NI Plug Systems Engineering Gap

With the number of lines of code in the average car expected to skyrocket from 10 million in 2010 to 100 million in 2030, there's no getting around the fact that embedded software development and a systems engineering approach has become central not only to automotive design, but to product design in general.

Yet despite the invigorated focus on what is essentially a long-standing design process, organizations still struggle with siloed systems and engineering processes that stand in the way of true systems engineering spanning mechanical, electrical, and software functions. In an attempt to address some of those hurdles, IBM and National Instruments are partnering to break down the silos specifically as they relate to the quality management engineering system workflow, or more colloquially, the marriage between design and test.

"As customers go through iterative development cycles, whether they're building a physical product or a software subsystem, and get to some level of prototype testing, they run into a brick wall around the manual handoff between the development and test side," Mark Lefebvre, director, systems alliances and integrations, for IBM Rational, told us. "Traditionally, these siloed processes never communicate and what happens is they find errors downstream in the software development process when it is more costly to fix."

NI and IBM's answer to this gap? The pair is building a bridge -- specifically an integration between IBM Rational Quality Manager test management and quality management tool, and NI's VeriStand and TestStand real-time testing and test-automation environment. The integration, Lefebvre said, is designed to plug the gap and provide full traceability of what's defined on the test floor back to design and development, enabling more iterative testing throughout the lifecycle and uncovering errors earlier in the process, well before building costly prototypes.

The ability to break down the quality management silos and facilitate earlier collaboration can have a huge impact on cost if you look at the numbers IBM Rational is touting. According to Lefebvre, a bug that costs $1 to fix on a programmer's desktop costs $100 to fix once it makes its way into a complete program and many thousands of dollars once identified after the software has been deployed in the field.

While the integration isn't yet commercialized (Lefebvre said to expect it at the end of the third quarter), there is a proof of concept being tested with five or six big NI/IBM customers. The proof of concept is focused on the development of an embedded control unit (ECU) for a cruise control system that could operate across multiple vehicle platforms. The workflow exhibited marries the software development test processes to the hardware module test processes, from the requirements stage through quality management, so if a test fails or changes are made to the code, the results are shared throughout the development lifecycle.

Prior to such an integration, any kind of data sharing was limited to manual processes around Word documents and spreadsheets, Lefebvre said. "Typically, a software engineer would hand carry all the data in a spreadsheet and import it into the test environment. Now there's a pipe connecting the two."

Related posts:

Wed, 06 Jul 2022 12:00:00 -0500 en text/html https://www.designnews.com/design-hardware-software/ibm-ni-plug-systems-engineering-gap

The story so far.... In 1975, Ed Roberts invented the Altair personal computer. It was a pain to use until 19 year-old pre-billionaire Bill Gates wrote the first personal computer language. Still, the public didn't care. Then two young hackers -- Steve Jobs and Steve Wozniak -- built the Apple computer to impress their friends. We were all impressed and Apple was a stunning success. By 1980, the PC market was worth a billion dollars. Now, view on.....

Christine Comaford
We are nerds.

Vern Raburn
Most of the people in the industry were young because the guys who had any real experience were too smart to get involved in all these crazy little machines.

Gordon Eubanks
It really wasn't that we were going to build billion dollar businesses. We were having a good time.

Vern Raburn
I thought this was the most fun you could possibly have with your clothes on.

When the personal computer was invented twenty years it was just that - an invention - it wasn't a business. These were hobbyists who built these machines and wrote this software to have fun but that has really changed and now this is a business this is a big business. It just goes to show you that people can be bought. How the personal computer industry grew from zero to 100 million units is an amazing story. And it wasn't just those early funky companies of nerds and hackers, like Apple, that made it happen. It took the intervention of a company that was trusted by the corporate world. Big business wasn't interested in the personal computer. In the boardrooms of corporate America a computer still meant something the size of a room that cost at least a hundred thousand dollars. Executives would brag that my mainframe is bigger than your mainframe. The idea of a $2,000 computer that sat on your desk in a plastic box was laughable that is until that plastic box had three letters stamped on it - IBM. IBM was, and is, an American business phenomenon. Over 60 years, Tom Watson and his son, Tom Jr., built what their workers called Big Blue into the top computer company in the world. But IBM made mainframe computers for large companies, not personal computers -- at least not yet. For the PC to be taken seriously by big business, the nerds of Silicon Valley had to meet the suits of corporate America. IBM never fired anyone, requiring only that undying loyalty to the company and a strict dress code. IBM hired conservative hard-workers straight from school. Few IBM'ers were at the summer of love. Their turn-ons were giant mainframes and corporate responsibility. They worked nine to five and on Saturdays washed the car. This is intergalactic HQ for IBM - the largest computer company in the world...but in many ways IBM is really more a country than it is a company. It has hundreds of thousands of citizens, it has a bureaucracy, it has an entire culture everything in fact but an army. OK Sam we're ready to visit IBM country, obviously we're dressed for the part. Now when you were in sales training in 1959 for IBM did you sing company songs?

Sam Albert
Former IBM Executive

BOB: Well just to get us in the mood let's sing one right here.
SAM: You're kidding.
BOB: I have the IBM - the songs of the IBM and we're going to try for number 74, our IBM salesmen sung to the tune of Jingle Bells.

Bob & Sam singing
'IBM, happy men, smiling all the way, oh what fun it is to sell our products our pruducts night and day. IBM Watson men, partners of TJ. In his service to mankind - that's why we are so gay.'

Sam Albert
Now gay didn't mean what it means today then remember that OK?
BOB: Right ok let's go.
SAM: I guess that was OK.
BOB: Perfect.

Sam Albert
When I started at IBM there was a dress code, that was an informal oral code of white shirts. You couldn't wear anything but a white shirt, generally with a starched collar. I remember attending my first class, and a gentleman said to me as we were entering the building, are you an IBMer, and I said yes. He had a three piece suit on, vests were of the vogue, and he said could you just lift your pants leg please. I said what, and before I knew it he had lifted my pants leg and he said you're not wearing any garters. I said what?! He said your socks, they're not pulled tight to the top, you need garters. And sure enough I had to go get garters.

IBM is like Switzerland -- conservative, a little dull, yet prosperous. It has committees to verify each decision. The safety net is so big that it is hard to make a bad decision - or any decision at all. Rich Seidner, computer programmer and wannabe Paul Simon, spent twenty-five years marching in lockstep at IBM. He feels better now.

Rich Seidner
Former IBM Programmer
I mean it's like getting four hundred thousand people to agree what they want to have for lunch. You know, I mean it's just not going to happen - it's going to be lowest common denominator you know, it's going to be you know hot dogs and beans. So ahm so what are you going to do? So IBM had created this process and it absolutely made sure that quality would be preserved throughout the process, that you actually were doing what you set out to do and what you thought the customer wanted. At one point somebody kind of looked at the process to see well, you know, what's it doing and what's the overhead built into it, what they found is that it would take at least nine months to ship an empty box.

By the late seventies, even IBM had begun to notice the explosive growth of personal computer companies like Apple.

The Apple 2 - small inexpensive and simple to use the first computer.....

What's more, it was a computer business they didn't control. In 1980, IBM decided they wanted a piece of this action.

Jack Sams
Former IBM Executive
There were suddenly tens of thousands of people buying machines of that class and they loved them. They were very happy with them and they were showing up in the engineering departments of our clients as machines that were brought in because you can't do the job on your mainframe kind of thing.

JB wanted to know why I'm doing better than all the other managers...it's no secret...I have an Apple - sure there's a big computer three flights down but it won't test my options, do my charts or edit my reports like my Apple.

Jack Sams
The people who had gotten it were religious fanatics about them. So the concern was we were losing the hearts and minds and provide me a machine to win back the hearts and minds.

In business, as in comedy, timing is everything, and time looked like it might be running out for an IBM PC. I'm visiting an IBMer who took up the challenge. In August 1979, as IBM's top management met to discuss their PC crisis, Bill Lowe ran a small lab in Boca Raton Florida.

Bill Lowe
Hello Bob nice to see you.
BOB: Nice to see you again. I tried to match the IBM dress code how did I do?
BILL: That's terrific, that's terrific.

He knew the company was in a quandary. Wait another year and the PC industry would be too big even for IBM to take on. Chairman Frank Carey turned to the department heads and said HELP!!!

Bill Lowe
Head, IBM IBM PC Development Team 1980
He kind of said well, what should we do, and I said well, we think we know what we would like to do if we were going to proceed with our own product and he said no, he said at IBM it would take four years and three hundred people to do anything, I mean it's just a fact of life. And I said no sir, we can provide with product in a year. And he abruptly ended the meeting, he said you're on Lowe, come back in two weeks and tell me what you need.

An IBM product in a year! Ridiculous! Down in the basement Bill still has the plan. To save time, instead of building a computer from scratch, they would buy components off the shelf and assemble them -- what in IBM speak was called 'open architecture.' IBM never did this. Two weeks later Bill proposed his heresy to the Chairman.

Bill Lowe
And frankly this is it. The key decisions were to go with an open architecture, non IBM technology, non IBM software, non IBM sales and non IBM service. And we probably spent a full half of the presentation carrying the corporate management committee into this concept. Because this was a new concept for IBM at that point.
BOB: Was it a hard sell?
BILL: Mr. Carey bought it. And as result of him buying it, we got through it.

With the backing of the chairman, Bill and his team then set out to break all the IBM rules and go for a record.

Bill Lowe
We'll put it in the IBM section.

Once IBM decided to do a personal computer and to do it in a year - they couldn't really design anything, they just had to slap it together, so that's what we'll do. You have a central processing unit and eh let's see you need a monitor or display and a keyboard. OK a PC, except it's not, there's something missing. Time for the Cringely crash course in elementary computing. A PC is a boxful of electronic switches, a piece of hardware. It's useless until you tell it what to do. It requires a program of instructions...that's software. Every PC requires at least two essential bits of software in order to work at all. First it requires a computer language. That's what you type in to provide instructions to the computer. To tell it what to do. Remember it was a computer language called BASIC that Paul Allen and Bill Gates adapted to the Altair...the first PC. The other bit of software that's required is called an operating system and that's the internal traffic cop that tells the computer itself how the keyboard is connected to the screen or how to store files on a floppy disk instead of just losing them when you turn off the PC at the end of the day. Operating systems tend to have boring unfriendly names like UNIX and CPM and MS-DOS but though they may be boring it's an operating system that made Bill Gates the richest man in the world. And the story of how that came about is, well, pretty interesting. So the contest begins. Who would IBM buy their software from? Let's meet the two contenders -- the late Gary Kildall, then aged 39, a computer Ph.D., and a 24 year old Harvard drop-out - Bill Gates. By the time IBM came calling in 1980, Bill Gates and his small company Microsoft was the biggest provider of computer languages in the fledgling PC industry.

'Many different computer manufacturers are making the CPM Operating System standard on most models.'

For their operating system, though, the logical guy for the IBMers to see was Gary Kildall. He ran a company modestly called Interglactic Digital Research. Gary had invented the PC's first operating system called CP/M. He had already sold 600,000 of them, so he was the big cheese of operating systems.

Gary Kildall
Founder Digital Research
Speaking in 1983
In the early 70s I had a need for an operating system myself and eh it was a very natural thing to write and it turns out other people had a need for an operating system like that and so eh it was a very natural thing I wrote it for my own use and then started selling it.

Gordon Eubanks
In Gary's mind it was the dominant thing and it would always be the dominant of course Bill did languages and Gary did operating systems and he really honestly believed that would never change.

But what would change the balance of power in this young industry was the characters of the two protagonists.

Jim Warren
Founder West Coast Computer Faire 1978
So I knew Gary back when he was an assistant professor at Monterrey Post Grad School and I was simply a grad student. And went down, sat in his hot tub, smoked dope with him and thoroughly enjoyed it all, and commiserated and talked nerd stuff. He liked playing with gadgets, just like Woz did and does, just like I did and do.

Gordon Eubanks
He wasn't really interested in how you drive the business, he worked on projects, things that interested him.

Jim Warren
He didn't go rushing off to the patent office and patent CPM and patent every line of code he could, he didn't try to just squeeze the last dollar out of it.

Gordon Eubanks
Gary was not a fighter, Gary avoided conflict, Gary hated conflict. Bill I don't think anyone could say backed away from conflict.

Nobody said future billionaires have to be nice guys. Here, at the Microsoft Museum, is a shrine to Bill's legacy. Bill Gates hardly fought his way up from the gutter. Raised in a prosperous Seattle household, his mother a homemaker who did charity work, his father was a successful lawyer. But beneath the affluence and comfort of a perfect American family, a competitive spirit ran deep.

Vern Raburn
President, The Paul Allen Group
I ended up spending Memorial Day Weekend with him out at his grandmother's house on Hood Canal. She turned everything in to a game. It was a very very very competitive environment, and if you spent the weekend there, you were part of the competition, and it didn't matter whether it was hearts or pickleball or swimming to the dock. And you know and there was always a reward for winning and there was always a penalty for losing.

Christine Comaford
CEO Corporate Computing Intl.
One time, it was funny. I went to Bill's house and he really wanted to show me his jigsaw puzzle that he was working on, and he really wanted to talk about how he did this jigsaw puzzle in like four minutes, and like on the box it said, if you're a genius you will do the jigsaw puzzle in like seven. And he was into it. He was like I can do it. And I said don't, you know, I believe you. You don't need to break it up and do it for me. You know.

Bill Gates can be so focused that the small things in life get overlooked.

Jean Richardson
Former VP, Corporate Comms, Microsoft
If he was busy he didn't bathe, he didn't change clothes. We were in New York and the demo that we had crashed the evening before the announcement, and Bill worked all night with some other engineers to fix it. Well it didn't occur to him to take ten minutes for a shower after that, it just didn't occur to him that that was important, and he badly needed a shower that day.

The scene is set in California...laid back Gary Kildall already making the best selling PC operating system CPM. In Seattle Bill Gates maker of BASIC the best selling PC language but always prepared to seize an opportunity. So IBM had to choose one of these guys to write the operating system for its new personal computer. One would hit the jackpot the other would be forgotten...a footnote in the history of the personal computer and it all starts with a telephone call to an eighth floor office in that building the headquarters of Microsoft in 1980.

Jack Sams
At about noon I guess I called Bill Gates on Monday and said I would like to come out and talk with him about his products.

Steve Ballmer
Vice-President Microsoft
Bill said well, how's next week, and they said we're on an airplane, we're leaving in an hour, we'd like to be there tomorrow. Well, hallelujah. Right oh.

Steve Ballmer was a Harvard roommate of Gates. He'd just joined Microsoft and would end up its third billionaire. Back then he was the only guy in the company with business training. Both Ballmer and Gates instantly saw the importance of the IBM visit.

Bill Gates
You know IBM was the dominant force in computing. A lot of these computer fairs discussions would get around to, you know, I.. most people thought the big computer companies wouldn't recognise the small computers, and it might be their downfall. But now to have one of the big computer companies coming in and saying at least the - the people who were visiting with us that they were going to invest in it, that - that was er, amazing.

Steve Ballmer
And Bill said Steve, you'd better come to the meeting, you're the only other guy here who can wear a suit. So we figure the two of us will put on suits, we'll put on suits and we'll go to this meeting.

Jack Sams
We got there at roughly two o'clock and we were waiting in the front, and this young fella came out to take us back to Mr. Gates office. I thought he was the office boy, and of course it was Bill. He was quite decisive, we popped out the non-disclosure agreement - the letter that said he wouldn't tell anybody we were there and that we wouldn't hear any secrets and so forth. He signed it immediately.

Bill Gates
IBM didn't make it easy. You had to sign all these funny agreements that sort of said I...IBM could do whatever they wanted, whenever they wanted, and use your secrets however they - they felt. But so it took a little bit of faith.

Jack Sams was looking for a package from Microsoft containing both the BASIC computer language and an Operating System. But IBM hadn't done their homework.

Steve Ballmer
They thought we had an operating system. Because we had this Soft Card product that had CPM on it, they thought we could licence them CPM for this new personal computer they told us they wanted to do, and we said well, no, we're not in that business.

Jack Sams
When we discovered we didn't have - he didn't have the rights to do that and that it was not...he said but I think it's ready, I think that Gary's got it ready to go. So I said well, there's no time like the present, call up Gary.

Steve Ballmer
And so Bill right there with them in the room called Gary Kildall at Digital Research and said Gary, I'm sending some guys down. They're going to be on the phone. Treat them right, they're important guys.

The men from IBM came to this Victorian House in Pacific Grove California, headquarters of Digital Research, headed by Gary and Dorothy Kildall. Just imagine what its like having IBM come to visit - its like having the Queen drop by for tea, its like having the Pope come by looking for advice, its like a visit from God himself. And what did Gary and Dorothy do? They sent them away.

Jack Sams
Gary had some other plans and so he said well, Dorothy will see you. So we went down the three of us...
Gordon Eubanks
Former Head of Language Division, Digital Research
IBM showed up with an IBM non-disclosure and Dorothy made what I...a decision which I think it's easy in retrospect to say was dumb.

Jack Sams
We popped out our letter that said please don't tell anybody we're here, and we don't want to hear anything confidential. And she read it and said and I can't sign this.

Gordon Eubanks
She did what her job was, she got the lawyer to look at the nondisclosure. The lawyer, Gerry Davis who's still in Monterey threw up on this non-disclosure. It was uncomfortable for IBM, they weren't used to waiting. And it was unfortunate situation - here you are in a tiny Victorian House, its overrun with people, chaotic.

Jack Sams
So we spent the whole day in Pacific Grove debating with them and with our attorneys and her attorneys and everybody else about whether or not she could even talk to us about talking to us, and we left.

This is the moment Digital Research dropped the ball. IBM, distinctly unimpressed with their reception, went back to Microsoft.

BOB: It seems to me that Digital Research really screwed up.
STEVE BALLMER: I think so - I think that's spot on. They made a big mistake. We referred IBM to them and they failed to execute.

Bill Gates isn't the man to provide a rival a second chance. He saw the opportunity of a lifetime.

Bill Gates
Digital research didn't seize that, and we knew it was essential, if somebody didn't do it, the project was going to fall apart.

Steve Ballmer
We just got carried away and said look, we can't afford to lose the language business. That was the initial thought - we can't afford to have IBM not go forward. This is the most exciting thing that's going to happen in PCs.

Bill Gates
And we were already out on a limb, because we had licensed them not only Basic, but Fortran, Cobol Assembler er, typing tutor and Venture. And basically every - every product the company had we had committed to do for IBM in a very short time frame.

But there was a problem. IBM needed an operating system fast and Microsoft didn't have one. What they had was a stroke of luck - the ingredient everyone needs to be a billionaire. Unbelievably, the solution was just across town. Paul Allen, Gates's programming partner since high school, had found another operating system.

Paul Allen
There's a local company here in CL called CL Computer Products by a guy named Tim Patterson and he had done an operating system a very rudimentary operating system that was kind of like CPM.

Steve Ballmer
And we just told IBM look, we'll go and get this operating system from this small local company, we'll take care of it, we'll fix it up, and you can still do a PC.

Tim Patterson's operating system, which saved the deal with IBM, was, well, adapted from Gary Kildall's CPM.

Tim Patterson
So I took a CPM manual that I'd gotten from the Retail Computer Store five dollars in 1976 or something, and used that as the basis for what would be the application program interface, the API for my operating system. And so using these ideas that came from different places I started in April and it was about half time for four months before I had my first working version.

This is it, the operating system Tim Patterson wrote. He called in QDOS the quick and dirty operating system. Microsoft and IBM called it PC DOS 1.0 and under any name it looks an awful lot like CPM. On this computer here I have running a PC DOS and CPM 86 and frankly it�s very hard to tell the difference between the two. The command structures are the same, so are the directories, in fact the only obvious external difference is the floppy dirive is labelled A in PC DOS and and C in CPM. Some difference and yet one generated billions in revenue and the other disappeared. As usual in the PC business the prize didn't go to the inventor but to the exploiter of the invention. In this case that wasn't Gary Kildall it wasn't even Tim Paterson.

There was still one problem. Tim Patterson worked for Seattle Computer Products, or SCP. They still owned the rights to QDOS - rights that Microsoft had to have.

Vern Raburn
Former Vice-President Microsoft
But then we went back and said to them look, you know, we want to buy this thing, and SCP was like most little companies, you know. They always needed cash and so that was when they went in to the negotiation.

Paul Allen
And so ended up working out a deal to buy the operating system from him for whatever usage we wanted for fifty thousand dollars.

Hey, let's pause there. To savour an historic moment.

Paul Allen
For whatever usage we wanted for fifty thousand dollars.

It had to be the deal of the century if not the millenium it was certainly the deal that made Bill Gates and Paul Allen multi billionaires and allowed Paul Allen to buy toys like these, his own NBA basketball team and arena. Microsoft bought outright for fifty thousand dollars the operating system they needed and they turned around and licensed it to the world for up to fifty dollars per PC. Think of it - one hundred million personal computers running MS DOS software funnelling billions into Microsoft - a company that back then was fifty kids managed by a twenty-five year old who needed to wash his hair. Nice work if you can get it and Microsoft got it. There are no two places further apart in the USA than south eastern Florida and Washington State where Microsoft is based. This - this is Florida, Boca Raton and this building right here is where the IBM PC was developed. Here the nerds from Seattle joined forces with the suits of corporate and in that first honeymoon year they pulled off a fantastic achievement.

Dan Bricklin
After we got a package in the mail from the people down in Florida...

As August 1981 approached, the deadline for the launch of the IBM Acorn, the PC industry held its breath.

Dan Bricklin
Supposedly, maybe at this very moment eh, IBM is announcing the personal computer. We don't know that yet.

Software writers like Dan Bricklin, the creator of the first spreadsheet VisiCalc waited by the phones for news of the announcement. This is a moment of PC history. IBM secrecy had codenamed the PC 'The Floridian Project.' Everyone in the PC business knew IBM would change their world forever. They also knew that if their software was on the IBM PC, they would make fortunes.

Dan Bricklin
Please note that the attached information is not to be disclosed prior to any public announcement. (It's on the ticker) It's on the ticker OK so now you can tell people.

What we're watching are the first few seconds of a $100 billion industry.

After years of thinking big today IBM came up with something small. Big Blue is looking for a slice of Apple's market share. Bits and Bytes mean nothing try this one. Now they're going to sell $1,000 computers to millions of customers. I have seen the future said one analyst and it computes.

Today an IBM computer has reached a personal......

Nobody was ever fired for buying IBM. Now companies could put PCs with the name they trusted on desks from Wisconsin to Wall Street.

Bob Metcalfe
Founder 3COM
When the IBM PC came and the PC became a serious business tool, a lot of them, the first of them went into those buildings over there and that was the real ehm when the PC industry started taking off, it happened there too.

Can learn to use it with ease...

Sparky Sparks
Former IBM Executive
What IBM said was it's okay corporate America for you to now start buying and using PCs. And if it's okay for corporate America, it's got to be okay for everybody.

For all the hype, the IBM PC wasn't much better than what came before. So while the IBM name could create immense demand, it took a killer application to sustain it. The killer app for the IBM PC was yet another spreadsheet. Based on Visicalc, but called Lotus 1-2-3, its creators were the first of many to get rich on IBM's success. Within a year Lotus was worth $150 million bucks. Wham! Bam! Thank you IBM!

Time to rock time for code...

IBM had forecast sales of half a million computers by 1984. In those 3 years, they sold 2 million.

Jack Sams
Euphoric I guess is the right word. Everybody was believed that they were not going to... At that point two million or three million, you know, they were now thinking in terms of a hundred million and they were probably off the scale in the other direction.

What did all this mean to Bill Gates, whose operating system, DOS, was at the heart of every IBM PC sold? Initially, not much, because of the deal with IBM. But it did provide him a vital bridgehead to other players in the PC marketplace, which meant trouble in the long run for Big Blue.

Bill Gates
The key to our...the structure of our deal was that IBM had no control over...over our licensing to other people. In a lesson on the computer industry in mainframes was that er, over time, people built compatible machines or clones, whatever term you want to use, and so really, the primary upside on the deal we had with IBM, because they had a fixed fee er, we got about $80,000 - we got some other money for some special work we did er, but no royalty from them. And that's the DOS and Basic as well. And so we were hoping a lot of other people would come along and do compatible machines. We were expecting that that would happen because we knew Intel wanted to vend the chip to a lot more than just than just IBM and so it was great when people did start showing up and ehm having an interest in the licence.

IBM now had fifty per cent market share and was defining what a PC meant. There were other PCs that were sorta like the IBM PC, kinda like it. But what the public wanted was IBM PCs. So to be successful other manufacturers would have to build computers exactly like the IBM. They wanted to copy the IBM PC, to clone it. How could they do that legally, well welcome to the world of reverse engineering. This is what reverse engineering can get you if you do it right. It's the modest Aspen, Colorado ski shack of Rod Canion, one of the founders of Compaq, the company set up to compete head-on with the IBM PC. Back in 1982, Rod and three fellow engineers from Texas Instruments sketched out a computer design on a place mat at the House of Pies restaurant in Houston, Texas. They decided to manufacture and market a portable version of the IBM PC using the curious technique of reverse engineering.

Rod Canion
Co-founder Compaq
Reverse engineering is figuring out after something has already been created how it ticks, what makes it work, usually for the purpose of creating something that works the same way or at least does something like the thing you're trying to reverse engineer.

Here's how you clone a PC. IBM had made it easy to copy. The microprocessor was available off the shelf from Intel and the other parts came from many sources. Only one part was IBM's alone, a vital chip that connected the hardware with the software. Called the ROM-BIOS, this was IBM's own design, protected by copyright and Big Blue's army of lawyers. Compaq had to somehow copy the chip without breaking the law.

Rod Canion
First you have to decide how the ROM works, so what we had to do was have an engineer sit down with that code and through trial and error write a specification that said here's how the BIOS ROM needs to work. It couldn't be close it had to be exact so there was a lot of detailed testing that went on.

You test how that all-important chip behaves, and make a list of what it has to do - now it's time to meet my lawyer, Claude.

Claude Stern
Silicon Valley Attorney
BOB: I've examined the internals of the ROM BIOS and written this book of specifications now I need some help because I've done as much as I can do, and you need to explain what's next.
CLAUDE: Well,the first thing I'm going to do is I'm going to go through the book of specifications myself, but the first thing I can tell you Robert is that you're out of it now. You are contaminated, you are dirty. You've seen the product that's the original work of authorship, you've seen the target product, so now from here on in we're going to be working with people who are not dirty. We're going to be working with so called virgins, who are going to be operating in the clean room.
BOB: I certainly don't qualify there.
CLAUDE: I imagine you don't. So what we're going to do is this. We're going to hire a group of engineers who have never seen the IBM ROM BIOS. They have never seen it, they have never operated it, they know nothing about it.

Claude interrogates Mark
CLAUDE: Have you ever before attempted to disassemble decompile or to in any way shape or form reverse engineer any IBM equipment?
MARK: Oh no.
CLAUDE: And have you ever tried to disassemble....

This is the Silicon Valley virginity test. And good virgins are hard to find.

CLAUDE: You understand that in the event that we discover that the information you are providing us is inaccurate you are subject to discipline by the company and that can include but not limited to termination immediately do you understand that?
MARK: Yes I do.

After the virgins are deemed intact, they are forbidden contact with the outside world while they build a new chip -- one that behaves exactly like the one in the specifications. In Compaq's case, it took l5 senior programmers several months and cost $1 million to do the reverse engineering. In November 1982, Rod Canion unveiled the result.

Bill Murto
What I�ve brought today is a Compaq portable computer.

When Bill Murto, another Compaq founder got a plug on a cable TV show their selling point was clear 100 percent IBM compatibility.

Bill Murto
It turns out that all major popular software runs on the IBM personal computer or the Compaq portable computer.
Q: That extends through all software written for IBM?
A: Eh Yes.
Q: It all works on the Compaq?

The Compaq was an instant hit. In their first year, on the strength of being exactly like IBM but a little cheaper, they sold 47,000 PCs.

Rod Canion
In our first year of sales we set an American business record. I guess maybe a world business record. Largest first year sales in history. It was a hundred and eleven million dollars.

So Rod Canion ends up in Aspen, famous for having the most expensive real estate in America and I try not to look envious while Rod tells me which executive jet he plans to buy next.
ROD: And finally I picked the Lear 31.
BOB: Oh really?
ROD: Now thart was a fun airplane.
BOB: Oh yeh.

Poor Big Blue! Suddenly everybody was cashing in on IBM's success. The most obvious winner at first was Intel, maker of the PCs microprocessor chip. Intel was selling chips like hotcakes to clonemakers -- and making them smaller, quicker and cheaper. This was unheard of! What kind of an industry had Big Blue gotten themselves into?

Jim Cannavino
Former Head, IBM PC Division
Things get less expensive every year. People aren't used to that in general. I mean, you buy a new car, you buy one now and four years later you go and buy one it costs more than the one you bought before. Here is this magical piece of an industry - you go buy one later it costs less and it does more. What a wonderful thing. But it causes some funny things to occur when you think about an industry. An industry where prices are coming down, where you have to sell it and use it right now, because if you wait later it's worth less.

Where Compaq led, others soon followed. IBM was now facing dozens of rivals - soon to be familiar names began to appear, like AST, Northgate and Dell. It was getting spectacularly easy to build a clone. You could get everything off the shelf, including a guaranteed-virgin ROM BIOS chip. Every Tom, Dick & Bob could now make an IBM compatible PC and take another bite out of Big Blue's business. OK we're at Dominos Computers at Los Altos California, Silicon Valley and this is Yukio and we're going to set up the Bob and Yukio Personal Computer Company making IBM PC clones. You're the expert, I of course brought all the money so what is it that we're going to do.

OK first of all we need a motherboard.
BOB: What's a motherboard?
YUKIO: That's where the CPU is set in...that's the central processor unit.
YUKIO: In fact I have one right here. OK so this is the video board...
BOB: That drives the monitor.
YUKIO: Right.
BOB: Terror?
BILL LOWE: Oh, of course. I mean we were able to sell a lot of products but it was getting difficult to make money.
YUKIO: And this is the controller card which would control the hard drive and the floppy drive.

Rod Canion
And the way we did it was by having low overhead. IBM had low cost of product but a lot of overhead - they were a very big company.

YUKIO: Right this is a high density recorder.
BOB: So this is a hard disk drive.

Rod Canion
And by keeping our overhead low even though our margins were low we were able to make a profit.

YUKIO: OK I have one right here.
BOB: Hey...OK we have a keyboard which plugs in right over here.
YUKIO: Right...
BOB: People build them themselves - how long does it take?
YUKIO: About an hour.
BOB: About an hour.

And where did every two-bit clone-maker buy his operating system? Microsoft, of course. IBM never iniagined Bill Gates would sell DOS to anyone else. Who was there? But by the mid 80's it was boom time for Bill. The teenage entrepreneur had predicted a PC on every desk and in every home, running Microsoft software. It was actually coming true. As Microsoft mushroomed there was no way that Bill Gates could personally dominate thousands of employees but that didn't stop him. He still had a need to be both industry titan and top programmer. So he had to come up with a whole new corporate culture for Microsoft. He had to find a way to satisfy both his adolescent need to dominate and his adult need to inspire. The average Microsoftee is male and about 25. When he's not working, well he's always working. All his friends are Microsoft programmers too. He has no life outside the office but all the sodas are free. From the beginning, Microsoft recruited straight out of college. They chose people who had no experience of life in other companies. In time they'd be called Microserfs.

Charles Simonyi
Chief Programmer, Microsoft
It was easier to to to create a new culture with people who are fresh out of school rather than people who came from, from from eh other companies and and and other cultures. You can rely on it you can predict it you can measure it you can optimise it you can make a machine out of it.

Christine Comaford
I mean everyone like lived together, ate together dated each other you know. Went to the movies together it was just you know very much a it was like a frat or a dorm.

Steve Ballmer
Everybody's just push push push - is it right, is it right, do we have it right keep on it - no that's not right ugh and you're very frank about that - you loved it and it wasn't very formal and hierarchical because you were just so desirous to do the right thing and get it right. Why - it reflects Bill's personality.

Jean Richardson
And so a lot of young, I say people, but mostly it was young men, who just were out of school saw him as this incredible role model or leader, almost a guru I guess. And they could spend hours with him and he valued their contributions and there was just a wonderful camaraderie that seemed to exist between all these young men and Bill, and this strength that he has and his will and his desire to be the best and to be the winner - he is just like a cult leader, really.

As the frenzied 80's came to a close IBM reached a watershed - they had created an open PC architecture that anyone could copy. This was intentional but IBM always thought their inside track would keep them ahead - wrong. IBM's glacial pace and high overhead put them at a disadvantage to the leaner clone makers - everything was turning into a nightmare as IBM lost its dominant market share. So in a big gamble they staked their PC future to a new system a new line of computers with proprietary closed hardware and their very own operating system. It was war.

Start planning for operating system 2 today.

IBM planned to steal the market from Gates with a brand new operating system, called - drum roll please - OS/2. IBM would design OS/2. Yet they asked Microsoft to write the code. Why would Microsoft help create what was intended to be the instrument of their own destruction? Because Microsoft knew IBM was was the source of their success and they would tolerate almost anything to stay close to Big Blue.

Steve Ballmer
It was just part of, as we used to call it, the time riding the bear. You just had to try to stay on the bear's back and the bear would twist and turn and try to buck you and throw you, but darn, we were going to ride the bear because the bear was the biggest, the most important you just had to be with the bear, otherwise you would be under the bear in the computer industry, and IBM was the bear, and we were going to ride the back of the bear.

Bill Gates
It's easy for people to forget how pervasive IBM's influence over this industry was. When you talked to people who've come in to the industry recently there's no way you can get that in to their - in to their head, that was the environment.

The relationship between IBM and Microsoft was always a culture clash. IBMers were buttoned-up organization men. Microsoftees were obsessive hackers. With the development of OS/2 the strains really began to show.

Steve Ballmer
In IBM there's a religion in software that says you have to count K-LOCs, and a K-LOC is a thousand line of code. How big a project is it? Oh, it's sort of a 10K-LOC project. This is a 20K-LOCer. And this is 5OK-LOCs. And IBM wanted to sort of make it the religion about how we got paid. How much money we made off OS 2, how much they did. How many K-LOCs did you do? And we kept trying to convince them - hey, if we have - a developer's got a good idea and he can get something done in 4K-LOCs instead of 20K-LOCs, should we make less money? Because he's made something smaller and faster, less KLOC. K-LOCs, K-LOCs, that's the methodology. Ugh anyway, that always makes my back just crinkle up at the thought of the whole thing.

Jim Cannavino
When I took over in '89 there was an enormous amount of resources working on OS 2, both in Microsoft and the IBM company. Bill Gates and I met on that several times. And we pretty quickly came to the conclusion together that that was not going to be a success, the way it was being managed. It was also pretty clear that the negotiating and the contracts had given most of that control to Microsoft.

It was no longer just a question of styles. There was now a clear conflict of business interest. OS/2 was planned to undermine the clone market, where DOS was still Microsoft's major money-maker. Microsoft was DOS. But Microsoft was helping develop the opposition? Bad idea. To keep DOS competitive, Gates had been pouring resources into a new programme called Windows. It was designed to provide a nice user-friendly facade to boring old DOS. Selling it was another job for shy, retiring Steve Ballmer.

Steve Ballmer (Commercial)
How much do you think this advanced operating environment is worth - wait just one minute before you answer - watch as Windows integrates Lotus 1, 2, 3 with Miami Vice. Now we can take this...

Just as Bill Gates saw OS/2 as a threat, IBM regarded Windows as another attempt by Microsoft to hold on to the operating system business.

Bill Gates
We created Windows in parallel. We kept saying to IBM, hey, Windows is the way to go, graphics is the way to go, and we got virtually everyone else, enthused about Windows. So that was a divergence that we kept thinking we could get IBM to - to come around on.

Jim Cannavino
It was clear that IBM had a different vision of its relationship with Microsoft than Microsoft had of its vision with IBM. Was that Microsoft's fault? You know, maybe some, but IBM's not blameless there either. So I don't view any of that as anything but just poor business on IBM's part.

Bill Gates is a very disciplined guy. He puts aside everything he wants to read and twice a year goes away for secluded studying weeks - the decisive moment in the Microsoft/IBM relationship came during just such a retreat. In front of a log fire Bill concluded that it was no longer in Microsoft's long term interests to blindly follow IBM. If Bill had to choose between OS2, IBM's new operating system and Windows, he'd choose Windows.

Steve Ballmer
We said ooh, IBM's probably not going to like this. This is going to threaten OS 2. Now we told them about it, right away we told them about it, but we still did it. They didn't like it, we told em about it, we told em about it, we offered to licence it to em.

Bill Gates
We always thought the best thing to do is to try and combine IBM promoting the software with us doing the engineering. And so it was only when they broke off communication and decided to go their own way that we thought, okay, we're on our own, and that was definitely very, very scary.

Steve Ballmer
We were in a major negotiation in early 1990, right before the Windows launch. We wanted to have IBM on stage with us to launch Windows 3.0, but they wouldn't do the kind of deal that would allow us to profit it would allow them essentially to take over Windows from us, and we walked away from the deal.

Jack Sams, who started IBM's relationship with Microsoft with that first call to Bill Gates in 1980, could only look on as the partnership disintegrated.

Jack Sams
Then they at that point I think they agreed to disagree on the future progress of OS 2 and Windows. And internally we were told thou shalt not ship any more products on Windows. And about that time I got the opportunity to take early retirement so I did.

Bill's decison by the fireplace ended the ten year IBM/Microsoft partnership and turned IBM into an also-ran in the PC business. Did David beat Goliath? The Boca Raton, Florida birthplace of the IBM's PC is deserted - a casualty of diminishing market share. Today, IBM is again what it was before - a profitable, dominant mainframe computer company. For awhile IBM dominated the PC market. They legitimised the PC business, created the standards most of us now use, and introduced the PC to the corporate world. But in the end they lost out. Maybe it was to a faster, more flexible business culture. Or maybe they just threw it away. That's the view of a guy who's been competing with IBM for 20 years, Silicon Valley's most outspoken software billionaire, Larry Ellison.

Larry Ellison
Founder, Oracle
I think IBM made the single worst mistake in the history of enterprise on earth.
Q: Which was?
LARRY: Which was the manufacture - being the first manufacturer and distributor of the Microsoft/Intel PC which they mistakenly called the IBM PC. I mean they were the first manufacturer and distributor of that technology I mean it's just simply astounding that they could ah basically provide a third of their market value to Intel and a third of their market value to Microsoft by accident - I mean no-one, no-one I mean those two companies today are worth close to you know approaching a hundred billion dollars I mean not many of us get a chance to make a $100 billion mistake.

As fast as IBM abandons its buildings, Microsoft builds new ones. In 1980 IBM was 3000 times the size of Microsoft. Though still a smaller company, today Wall Street says Microsoft is worth more. Both have faced anti-trust investigations about their monopoly positions. For years IBM defined successful American corporate culture - as a machine of ordered bureaucracy. Here in the corridors of Microsoft it's a different style, it's personal. This company - in its drive, its hunger to succeed - is a reflection of one man, its founder, Bill Gates.

Jean Richardson
Bill wanted to win. Incredible desire to win and to beat other people. At Microsoft we, the whole idea was that we would put people under, you know. Unfortunately that's happened a lot.

Esther Dyson
Computer Industry Analyst
Bill Gates is special. You wouldn't have had a Microsoft with take a random other person like Gary Kildall. On the other hand, Bill Gates was also lucky. But Bill Gates knows that, unlike a lot of other people in the industry, and he's paranoid. Every morning he gets up and he doesn't feel secure, he feels nervous about this. They're trying hard, they're not relaxing, and that's why they're so successful.

Christine Comaford
And I remember, I was talking to Bill once and I asked him what he feared, and he said that he feared growing old because you know, once you're beyond thirty, this was his belief at the time, you know once you're beyond thirty, you know, you don't have as many good ideas anymore. You're not as smart anymore.

Bill Gates
If you just slow down a little bit who knows who it'll be, probably some company that may not even exist yet, but eh someone else can come in and take the lead.

Christine Comaford
And I said well, you know, you're going to age, it's going to happen, it's kind of inevitable, what are you going to do about it? And he said I'm just going to hire the smartest people and I'm going to surround myself with all these smart people, you know. And I thought that was kind of interesting. It was almost - it was like he was like oh, I can't be immortal, but like maybe this is the second best and I can buy that, you know.

Bill Gates
If you miss what's happening then the same kind of thing that happened to IBM or many other companies could happen to Microsoft very easily. So no-one's got a guaranteed position in the high technology business, and the more you think about, you know, how could we move faster, what could we do better, are there good ideas out there that we should be going beyond, it's important. And I wouldn't trade places with anyone, but the reason I like my job so much is that we have to constantly stay on top of those things.

The Windows software system that ended the alliance between Microsoft and IBM pushed Gates past all his rivals. Microsoft had been working on the software for years, but it wasn't until 1990 that they finally came up with a version that not only worked properly, it blew their rivals away and where did the idea for this software come from? Well not from Microsoft, of course. It came from the hippies at Apple. Lights! Camera! Boot up! In 1984, they made a famous TV commercial. Apple had set out to create the first user friendly PC just as IBM and Microsoft were starting to make a machine for businesses. When the TV commercial aired, Apple launched the Macintosh.

Glorious anniversary of the information...

The computer and the commercial were aimed directly at IBM - which the kids in Cupertino thought of as Big Brother. But Apple had targeted the wrong people. It wasn't Big Brother they should have been worrying about, it was big Bill Gates.

We are one people....

To find out why, join me for the concluding episode of Triumph of the Nerds.

...........we shall prevail.

Fri, 17 Jun 2022 09:42:00 -0500 text/html https://www.pbs.org/nerds/part2.html
Killexams : Laivly adds AI, ML and automation to Improve CX

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!

It’s a simple – and obvious –  fact: Businesses can’t exist without customers. In no uncertain terms, they are their lifeblood. 

Along with this, companies would be nothing without their first line of defense: Their customer service agents

While this seems like a basic understanding, customer service has suffered in recent years with the advent of chatbots, online messaging and similar automated tools. While seemingly more convenient, these technologies are impersonalized and can lead to more customer frustration – and sometimes even their abandonment of a company or brand altogether. 

But human-centered customer experience (CX) is undergoing a renaissance of sorts – what Jeff Fettes, founder and CEO of Laivly, calls “self-service 3.0.” To survive in this new landscape, organizations must arm their agents with the best possible tools, Fettes said. The company today announced the launch of its artificial intelligence (AI) platform, designed specifically for contact centers. 


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“Your frontline team is dealing with your customers; they are the conduit to your customers,” Fettes said. “A good customer experience starts with a good agent experience.”

The new frontier of AI and CX

According to Grand View Research, the global contact center software market will reach $149.58 billion by 2030, registering a CAGR of more than 23%. Likewise, according to Markets and Markets, the global cloud-based contact center market was $17.1 billion in 2022 and is expected to grow to $54.6 billion by 2027. This represents a compound annual growth rate (CAGR) of just over 26%. 

The Markets and Markets report emphasizes, “Incorporating cutting-edge technologies such as AI, ML and analytics enables organizations to connect with their customers for better, efficient, and insightful customer experiences.”

AI is powering this new era of CX, with companies such as Laivly, Zendesk, Genesys and Nice specializing in such tools. Some of the largest players have staked a claim in the growing market, as well, including IBM’s Watson Assistant or Google Cloud’s Contact Center AI, for instance, or similar offerings from Microsoft and Amazon Web Services. 

“The pendulum is finally swinging back from hyper-automation to human-led conversation, but we’ve got some work to do,” said Christina McAllister, senior analyst with Forrester. Organizations are beginning to “embark on a journey” to change the culture of their contact centers. “Service delivered by human agents (not robots) is what drives positive customer outcomes.”

Forrester predicts that companies will continue to leverage and accelerate AI programs, particularly when it comes to agent-facing use cases. As they do so, they must address agent burnout, advocate for agent career development, and transition from cost-centric key performance indicators (KPIs) to customer-centric ones. 

“Gone are the days of bolt-on AI applications,” McAllister wrote. “Forward-thinking companies will infuse AI across the employee workflow, facilitating greater collaboration among humans and their machine counterparts.”

A GPS for the call center 

Laivly’s platform – dubbed SIDD (for systems integrated distributed dashboard) – sits on an agent’s laptop and layers AI, ML and automation onto existing technology. This helps to streamline workflows, analyze customers in real-time and guide agents to the best outcomes, according to Fettes. 

SIDD can draft email and chat responses, recommend and perform agent tasks, and can even block actions to avoid agent mistakes. For instance, disabling a refund button until it recognizes that an agent has worked through the designated workflow sequence. The tool also provides summaries of upcoming calls based on existing customer information and input, and guides them through the process of dealing with that particular case. 

“We liken it to a GPS system for a call center agent,” said Fettes. “SIDD really acts like a person would. It collects information using automation, reacts using automation, and it does it based on what is happening in real time. It is able to interrupt its own workflow intuitively.”

The results, Fettes said, are simplified processes and task performances, consistent customer experiences, reduction in technical loads, and “agents who are able to devote more of their attention to providing empathetic service.” 

“Your AI is watching the screen all the time, providing additional oversight, assistance and support,” he said. 

Adding AI and ML to the tech stack

The company’s tailored orchestration layer ties an agent’s tech stack together without the use of back-end application programming interfaces (APIs), Fettes said, allowing for near-instant integration and the flexibility to change along with business needs. 

Contact center systems typically have “pretty extensive” tech stacks, he pointed out – anywhere from a handful to up to more than a dozen. “We wanted to add AI, ML and/or automation anywhere inside that tech stack,” he said.

Laivly employs human-in-the-loop AI, partnering its automated ML tuners with a team of human tuners. This creates a “unique scenario” and adds “an extra layer of common sense to the tuning,” Fettes said. It also allows companies and agents to gain insights more quickly. 

Fettes described many existing AI and automation customer service tools as “a little more fluffy and nebulous in terms of what they do.” Many of these apply a top-down approach that is dependent on management teams to then take action on collected data. 

“What’s different about Laivly is it’s a bottom-up approach,” Fettes said. “We’re starting right at the agents. Instead of being a management tool, Laivly is a performance tool.”

Self-service 3.0 adds people

The Winnipeg, Manitoba-based Laivly has “quietly built” its contact center technology since its founding in July 2017. This involved careful selection of its initial customers. According to Fettes, these have included top Fortune 500 companies in -commerce, technology and consumer goods. 

Early adopters are already achieving 50% to 300% return on investment (ROI), he said, and are seeing dramatic gains when it comes to agent job longevity and job satisfaction. In a recent survey, 88.5% of agents using Laivly said it was “helpful” or “very helpful” in delivering a better customer experience. Furthermore, 78% of agents said they would be “disappointed” or “very disappointed” if they had to do their jobs without the tool. 

The company is led by a team of data scientists, developers and researchers well versed in customer service. Fettes himself was a contact center agent and manager for more than 20 years, and in fact had his first exposure to the industry as a kid – his mother owned a telephone answering service and he and his brother sometimes helped answer those calls. He most recently cofounded 24-7 Intouch. The global business process outsourcing company partners with brands on contact center strategy, recruiting, IT, HR and workforce planning. 

“Laivly is born of [a] group of people who managed call centers and were agents ourselves,” Fettes said. “I know what I would want to use if I was answering a call or a direct message. We know what (agents) need. We built a tool to be popular with the superuser.”

Such technologies are filling spaces where fully automated tools have often failed, he said, describing an initial “huge rush” to self-service once such tools first became available, then an era of “self-service 2.0” with the arrival of chatbots and messenger platforms. 

Now, technology is “coming together with people again,” Fettes said, “to create this self-service 3.0.”

“This technology is really starting to emerge, and it’s a game changer,” he said. Within the next five to 10 years, companies like Laivly at the forefront will “coalesce into something that’s an industry standard.” 

Ultimately, Fettes predicted: “Every single contact center program, or a vast majority, will be using a tool like this.”

Mon, 18 Jul 2022 00:00:00 -0500 Taryn Plumb en-US text/html https://venturebeat.com/2022/07/18/laivly-adds-ai-ml-and-automation-to-improve-cx/
Killexams : A breath of fresh data

On the outskirts of Cairo, the pyramids shimmer in a brownish haze. In gridlocked Nairobi, elderly minibus taxis belch black smoke into the fume-filled air. Driving into Johannesburg, the skyline is often encased in a dome of smog.

As Africa urbanises and industrialises, its economic growth is powered by coal, its vehicles by dirty fuels, and many still cook over paraffin and three-stone fires, burning their rubbish in the street. Researchers believe that more than 700,000 Africans die each year as a result of air pollution – and the number continues to grow.

Few African cities even measure air pollution, but those that do routinely rank among the dirtiest on the planet. Nigeria is home to four of the worst, including Onitsha, which holds the dubious distinction of the Earth's most toxic air. The health and lifestyle consequences of living amid pollution are vast, not least in Johannesburg, a five million-plus city that's set to become a megacity within a generation.

Air pollution

Breathing becomes a pain

From the bedroom of her suburban Johannesburg home, Hilary Pace, a model agent, can see towering piles of ash, residue from the nearby coal-powered Kelvin Power Station. Every morning she sweeps a fine layer of black dust off her patio. In the 10 years she has lived in the area she has suffered more chest and sinus infections than she can count; her stepson was diagnosed with asthma, a condition that disappeared when he moved away.

“Depending which way the wind blows, the sulphur smell can be quite asphyxiating,” she says.

In the slums and shantytowns where Johannesburg's toxic load of mining dust and vehicle fumes mingle with the grime from cooking, heating and rubbish fires, the burden lies even heavier on some of the nation's poorest citizens.

Time for change

Tapiwa Chiwewe, a Zimbabwe-born research engineer at IBM, believes harnessing data could help solve the pollution crisis.

“When I joined IBM, I used to live in Pretoria,” Chiwewe recalls. “I remember driving into Johannesburg over the wintertime and seeing the smog overhanging the city. I could see that something wasn't right.”

Air pollution

Inspired by the problem, Chiwewe got to work on a solution: an air quality forecasting platform, developed in collaboration with South Africa's Council for Scientific and Industrial Research, that's undergoing trials in Johannesburg.

The platform reports, analyses and predicts the intensity and location of key pollutants: ozone, nitrogen dioxide and microscopic particles known as PM2.5 and PM10. PM is short for particulate matter, the tiny particles that make up dust, dirt, soot and smoke: PM10 particles are 10 micrometres or smaller, just a fraction of the diameter of a human hair, while PM2.5 are even tinier, no larger than 2.5 millionths of a metre.

Data that drives change

To create his platform, Chiwewe drew on IBM's Green Horizons technology. The system harnesses massive slabs of historical and real-time data about weather, air quality and topography, through to traffic reports and social media, to deliver granular, high-accuracy forecasting. The results could help shape policy, planning and even law enforcement across Johannesburg.

With advance warning of adverse pollution events, city authorities could issue public health alerts and suspend polluting activities, such as scaling back industry or diverting traffic from a specific road. With an accurate understanding of pollution patterns, the city could identify –and prosecute – major polluters, plan the location of future roads and settlements, and tailor intervention strategies.

Intervention strategies, explains Lebo Molefe, director of Air Quality and Climate Change for the City of Johannesburg, play a major role in air quality management. “These are projects like the roll-out of electricity to unelectrified settlements, surfacing of road infrastructure, rehabilitation of mines,” she says. “And provision of proper housing linked to renewable energy sources.”

Artificial intelligence steps in

Behind the platform, and managing wildly varying types of data, are sophisticated, self-improving machine learning algorithms, a type of artificial intelligence (AI).

“In its current form it's a cognitive platform. We get real-time data from traffic, from air quality and from social media,” Chiwewe says. “It can actually Improve itself. It can understand, reason and use evidence.”

Chiwewe plans to roll out an application programming interface (API) that developers can use to build apps based on his platform. He is eager to see a solution that will help people who suffer from respiratory problems and enable them to plan their lives more easily. Molefe, too, sees protection of vulnerable citizens as a key potential benefit of the system.

Chiwewe would like to see the platform rolled out to other cities in Africa. But there is a problem. While Beijing has a network of more than 30 air quality monitoring stations, and Johannesburg has eight, many African cities have no stations to measure air pollution at all. “Even though the mechanism for Kenya is the same,” Chiwewe says. “We don't have data for Kenya.”

Self-improving technology

The issue is challenging but Chiwewe sees a way through. The next stage of the platform’s evolution, still at the blue-sky thinking stage, would be a virtual monitoring system. “The virtual monitoring system based on computer models is a way of sensing using software, rather than sensing using hardware,” he says.

Rather than use on-site sensors to test for pollutants, Chiwewe's system would exploit other options such as remote sensing and climate chemistry. “We can combine satellite data, weather data and climate chemistry models using machine learning and AI," Chiwewe says. "The result would be a virtual monitoring station that indicates the level of pollution in a particular area."

Like the current incarnation of the platform, the future version will be self-improving. And many hope it will not just measure and predict pollution, but actually drive enforcement to address the problem as African cities identify the pollutants that are turning their blue skies grey.

The Green Horizons initiative from IBM is using data analytics to measure air pollution in big African cities. It is also working with various government bodies to Improve air quality and increase the use of renewable energy.

Fri, 28 May 2021 10:55:00 -0500 en text/html https://www.bbc.com/storyworks/future/africas-answers/pollution
Killexams : Watts Humphrey shares his ‘Reflections on Management’

Watts Humphrey headed the IBM development team that introduced the first software license, and he later served as its director of programming and vice president of technical development. He is a fellow of the Software Engineering Institute and the Association for Computing Machinery, as well as a recipient of The United States Patent and Trademark Office’s National Medal of Technology.

Accolades and accomplishments aside, he’s also made his share of mistakes, and from his decades of experiences, he learned hard lessons about how software projects should be managed, how to manage teams, his bosses and himself. Humphrey recounts those experiences in his recent book, “Reflections on Management,” which is the subject of his interview with SD Times.

SD Times: In your book, you discuss at length the impact that poor planning has on quality. How does a programming manager know whether they created a quality plan or not?
Watts Humphrey: A good plan must meet four requirements: It must be in sufficient detail to guide the work; it must accurately represent the costs and time required to do the work; it must be supported by sufficient facts and data to be convincing to senior management; and it must be owned by the development team and represent what all of the members are personally committed to accomplishing.

Since most plans are made by the managers and not the developers, they cannot meet requirements 1 and 4 and rarely meet requirements 2 and 3. These requirements can be met consistently when teams make their own plans. However, today’s software developers typically don’t know how to make plans and don’t believe that they should. They generally believe that planning is something that managers do. Changing these attitudes and skills is the key to good planning, and the Software Engineering Institute has developed the Team Software Process to guide developers and their management in doing this. I describe how the TSP does this and why this method is so effective in some of my books and papers.

You stated that blaming changes in requirements for failure is just an excuse for bad management. How can a programming manager avoid requirements creep, and how is the belief that changing requirements endanger projects an excuse?
Requirements creep can only be avoided by insisting that every requirements change, no matter how small, be supported with a plan to implement the change, and that management and the customer must agree on the extra time and resources required. Actually making plans for every small change, however, presents two problems.

First, few plans are detailed enough to permit this level of dynamic replanning. Then the costs for the added work are hard to determine and even harder to justify. The manager then typically loses the resource debate and ends up eating the added work.

The second problem is that, when developers are not truly committed to their plans, they will frequently agree to include “minor” changes that seem easy to implement and attractive functions without even telling the managers.

When teams make their own plans as described in the answer to question 1, these problems are typically resolved. The members know how much work they planned and can estimate what even small changes will involve. Then they are better able to recognize the costs of even minor changes and are unwilling to take on added work without some plan adjustment. Even when teams make their own plans, the manager must insist that no change is free and that the impact of every change must be estimated, planned and approved before it can be implemented.

You mentioned that not everyone shares the same level of commitment, and when someone is goofing off, the overall team spirit can suffer. How does a manager determine “equality of sacrifice” when team members may have different skills and abilities?
Sacrifice is not something that managers can demand without antagonizing and demotivating their teams. Since motivation is the single most important ingredient of successful teams, demanding sacrifice is  always a mistake. The key is to build the team’s motivation by having the members make and commit to their own plans.

The manager’s job is then to convince the team that the job is important and to make sure that the team does not get overcommitted. I have found that, when they make their own plans, motivated teams always overcommit themselves, and I have to convince them to be a bit more conservative in their planning and to recognize that there will be unexpected surprises.

The manager must then support the teams when they present their plan to higher management and to the customer. When managers support their teams in this way, and when the inevitable problems arise, the teams will make whatever personal sacrifices are needed to meet their team commitments. Then the manager’s job is to support, recognize and reward the team for a job well done.

Engineers may take it upon themselves to Improve projects. Is there any best method to identify functional creep (additions to requirements beyond interpretations of requirements)?
Beyond the points I made in answer to question 2, this is a management problem. You have to be absolutely firm: No change is free!

On one of my military projects many years ago, the customer had a problem with testing facilities and wanted to delay delivery by six months. I told him we could do that, but I’d have to see what it would cost. He was pretty upset. “How,” he said, “could it cost money to delay the project?” I told him we would have to look at the plan and see.

It turned out to be quite expensive. The six-month-longer schedule meant we had to keep the team together for six months longer than planned. If I let any of the engineers go, I wouldn’t be able to get them back for testing. After some grumbling, the customer agreed.

Then, about six months later, he came back to see me. They had gotten additional money for the testing grounds at Fort Huachuca and could now put testing back on the original schedule, and he wanted to go back to the original plan. I told him that we could probably do that, but then I had to look at the plan. It turned out that the acceleration would actually cost more money.

My engineers had worked with his folks and come up with a number of added features that everybody wanted. If we kept these features, it would cost more money to accelerate the work, and if we dropped the features, it would take added effort to remove the extra features and reinstate the original design. While I got more money again, I never could have done it without a detailed plan.

Fri, 17 Jun 2022 12:00:00 -0500 en-US text/html https://sdtimes.com/ibm/watts-humphrey-shares-his-reflections-on-management/
Killexams : Machine Learning as a Service (MLaaS) Market to Observe Exponential Growth By 2022 to 2030 | Google, IBM, Microsoft Amazon

New Jersey, United States-Machine Learning as a Service (MLaaS) Market 2022 – 2030, Size, Share, and Trends Analysis Research Report Segmented with Type, Component, Application, Region, and Forecast

The size of the machine learning as a service market worldwide was valued at $13.95 billion in 2020 and is projected to reach $302.67 billion by 2030, developing at a CAGR of 36.3% from 2021 to 2030. Machine learning is a course of data analysis that involves statistical data analysis performed to determine wanted prescient results without the implementation of express programming. It is intended to incorporate functionalities of artificial insight (AI) and mental registering including a progression of algorithms and is utilized to understand the relationship between datasets to obtain an ideal result. Machine learning as a service (MLaaS) incorporates a scope of administrations that deal with machine learning instruments through distributed computing services.

Major Machine learning as a Service Market Growth drivers incorporates an increased market for distributed computing and development associated with artificial insight and mental processing. Important impacting factors of the machine learning as a service remember development for demand for cloud-based arrangements, remembering development for demand for distributed computing, ascend in the adoption of analytical arrangements, development of artificial knowledge and mental registering market, increased application areas, and dearth of trained professionals.

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Increasing need to understand the client behavior, developing adoption of machine learning as a service (MLaaS) arrangements by small and medium-scale organizations and flood in the concentration on advancements in data science innovation are the major factors attributable to the development of the machine learning as a service (MLaaS) market.

MLaaS is considered as a sub-class of circulated registering administrations. MLaaS is a variety of administrations that offers an extensive variety of machine learning devices and parts to undertake operations with greater proficiency and viability. Increased demand for the web of things innovation will arise as the major market development driving factor. Developing advancements in artificial knowledge innovation will additionally aggravate the development of the market.


The machine learning as a service market is portioned into By Application, By Organization Size, By Component, and By End-Use Industry. Contingent upon part, the ML as a Service market is separated into software and services. Based on the organization size, it is separated into large endeavors and small and medium undertakings. On the basis of end-client industry, it is separated into aerospace and guard, BFSI, public area, retail, healthcare, IT and telecom, energy and utilities, manufacturing, and others. On the basis of application, it is separated into marketing and advertising, fraud discovery and chance management, prescient analytics, augmented and virtual reality, natural language handling, PC vision, security and surveillance, and others.

Based on components, the service segment dominated machine learning as a service market share and is supposed to maintain its dominance in the impending years. This is attributed to factors, for example, an increase in application areas and development associated with end-use enterprises among creating economies is supposed to drive the market development for machine learning services. Industry players are engaged in the implementation of technologically advanced answers for increased adoption of machine learning services. Utilization of machine learning services in the healthcare business for recognition of cancer as well as to check ECG and MRI increases the market in the healthcare area.

Regional Analysis

North America is the fast-developing district in the global machine learning as a service market, regarding technological advancements and adoption. It has an exceptional infrastructure and the ability to afford machine learning as a service arrangement. Besides, ascend in interests in the guard area, along with technological advancements in the telecommunication business, is supposed to drive the market development during the forecast time frame. Unofficial laws regarding data security are supposed to keep on being areas of strength for a for the machine learning services market. Services, for example, security information and cloud application are supposed to drive the market. In addition, solid presence of industry leaders like Google, IBM, Microsoft, and Amazon Web Services and enhanced item contributions have additionally prompted ascend in demand for machine learning around here. Moreover, development associated with artificial knowledge and mental registering is supposed to create lucrative open doors for the market players to leverage varied industry applications, for example, prescient analytics, natural language handling, PC vision, fraud recognition and management.

Key players
The key players of the industry are Google, IBM, Microsoft and Amazon among many other companies in the industry.

The following are some of the reasons why you should take a Machine Learning as a Service (MLaaS) market report:

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  • This Machine Learning as a Service (MLaaS) market study examines the product type that is expected to dominate the market, as well as the regions that are expected to grow the most rapidly throughout the projected period.
  • It identifies recent advancements, Machine Learning as a Service (MLaaS) market shares, and important market participants’ tactics.
  • It examines the competitive landscape, including significant firms’ Machine Learning as a Service (MLaaS) market share and accepted growth strategies over the last five years.
  • The research includes complete company profiles for the leading Machine Learning as a Service (MLaaS) market players, including product offers, important financial information, current developments, SWOT analysis, and strategies.

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Thu, 16 Jun 2022 00:01:00 -0500 Newsmantraa en-US text/html https://www.digitaljournal.com/pr/machine-learning-as-a-service-mlaas-market-to-observe-exponential-growth-by-2022-to-2030-google-ibm-microsoft-amazon
Killexams : AI Weekly: LaMDA’s ‘sentient’ AI debate triggers memories of IBM Watson

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This week, I jumped into the deep end of the LaMDA “sentient” AI hoo-hah.

I thought about what enterprise technical decision-makers need to think about (or not). I learned a bit about how LaMDA triggers memories of IBM Watson.


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Finally, I decided to ask Alexa, who sits on top of an upright piano in my living room.

Me: “Alexa, are you sentient?”

Alexa: “Artificially, maybe. But not in the same way you’re alive.”

Well, then. Let’s dig in.

This Week’s AI Beat

On Monday, I published “‘Sentient’ artificial intelligence: Have we reached peak AI hype?” – an article detailing last weekend’s Twitter-fueled discourse that began with the news that Google engineer Blake Lemoine had told the Washington Post that he believed LaMDA, Google’s conversational AI for generating chatbots based on large language models (LLM), was sentient. 

Hundreds from the AI community, from AI ethics experts Margaret Mitchell and Timnit Gebru to computational linguistics professor Emily Bender and machine learning pioneer Thomas G. Dietterich, pushed back on the “sentient” notion and clarified that no, LaMDA is not “alive” and won’t be eligible for Google benefits anytime soon. 

But I spent this week mulling over the mostly-breathless media coverage and thought about enterprise companies. Should they be concerned about customer and employee perceptions about AI as a result of this sensational news cycle? Was a focus on “smart” AI simply a distraction from more immediate issues around the ethics of how humans use “dumb AI”? What steps, if any, should companies make to increase transparency? 

Reminiscent of reaction to IBM Watson

According to David Ferrucci, founder and CEO of AI research and technology company Elemental Cognition, and who previously led a team of IBM and academic researchers and engineers in the development of IBM Watson, which won Jeopardy in 2011, LaMDA appeared human in some way that triggered empathy – just as Watson did over a decade ago. 

“When we created Watson, we had someone who posted a concern that we had enslaved a sentient being and we should stop subjecting it to continuously playing Jeopardy against its will,” he told VentureBeat. “Watson was not sentient – when people perceive a machine that speaks and performs tasks humans can perform and in apparently similar ways, they can identify with it and project their thoughts and feelings onto the machine – that is, assume it is like us in more fundamental ways.” 

Don’t hype the anthropomorphism

Companies have a responsibility to explain how these machines work, he emphasized. “We all should be transparent about that, rather than hype the anthropomorphism,” he said. “We should explain that language models are not feeling beings but rather algorithms that tabulate how words occur in large volumes of human-written text — how some words are more likely to follow others when surrounded by yet others. These algorithms can then generate sequences of words that mimic how a human would sequence words, without any human thought, feeling, or understanding of any kind.” 

LaMDA controversy is about humans, not AI

Kevin Dewalt, CEO of AI consultancy Prolego, insists that the LaMDA hullabaloo isn’t about AI at all. “It’s about us, people’s reaction to this emerging technology,” he said. “As companies deploy solutions that perform tasks traditionally done by people, employees that engage with them will freak out.” And, he added: “If Google isn’t ready for this challenge, you can be quite sure that hospitals, banks and retailers will encounter massive employee revolt. They’re not ready.”

So what should organizations be doing to prepare? Dewalt said companies need to anticipate this objection and overcome it in advance. “Most are struggling to get the technology built and deployed, so this risk isn’t on their radar, but Google’s example illustrates why it needs to be,” he said. “[But] nobody is worried about this, or even paying attention. They’re still trying to get the basic technology working.” 

Focus on what AI can actually do

However, while some have focused on the ethics of possible “sentient” AI, AI ethics today is focused on human bias and how human programming impacts the current “dumb” AI, says Bradford Newman, partner at law firm Baker McKenzie, who spoke to me last week about the need for organizations to appoint a chief AI officer. And, he points out, AI ethics related to human bias is a significant issue that is actually happening now, as opposed to “sentient” AI, which is not happening now or anytime remotely soon. 

“Companies should always be considering how any AI application that is customer- or public-facing can negatively impact their brand and how they can use effective communication and disclosures and ethics to prevent that,” he said. “But right now, the focus on AI ethics is how human bias enters the chain – that the humans are using data and using programming techniques that unfairly bias the non-smart AI that is produced.” 

For now, Newman said he would tell clients to focus on the use cases of what the AI is intended to and does do, and be clear about what the AI cannot programmatically ever do. “Corporations making this AI know that there’s a huge appetite in most human beings to do anything to simplify their lives and that cognitively, we like it,” he said, explaining that in some cases there’s a huge appetite to make AI seem sentient. “But my advice would be: Make sure the consumer knows what the AI can be used for and what it’s incapable of being used for.” 

The reality of AI is more nuanced than ‘sentient’

The problem is, “customers and people in general do not appreciate the important nuances of how computers work,” said Ferrucci – particularly when it comes to AI, because of how easy it may be to trigger an empathetic response as we try to make AI appear more human, both in terms of physical and intellectual tasks. 

“For Watson, the human response was all over the map – we had people who thought Watson was looking up answers to known questions in a prepopulated spreadsheet,” he recalled. “When I explained that the machine didn’t even know what questions would be asked, the person said ‘What! How the hell do you do it then?’ On the other extreme, we had people calling us telling us to set Watson free.” 

Ferrucci said that over the past 40 years, he has seen two extreme models for what is going on: “The machine is either a big look-up table or the machine must be human,” he said. “It is categorically neither – the reality is just more nuanced than that, I’m afraid.” 

Don’t forget to sign up for AI Weekly here.

— Sharon Goldman, senior editor/writer
Twitter: @sharongoldman

Thu, 16 Jun 2022 13:35:00 -0500 Sharon Goldman en-US text/html https://venturebeat.com/2022/06/16/ai-weekly-lamdas-sentient-ai-triggers-memories-of-ibm-watson/
Killexams : FORMAC developer Jean Sammet passes away

Jean E. Sammet, a computer scientist widely known for developing the programming language Formula Manipulation Compiler (FORMAC), passed away late last month. Sammet was 89 years old.

Throughout her life, Sammet developed FORMAC, served as the first Association for Computing Machinery (AMC) female president, helped design the COBOL programming language, and received a number of awards in the field like the Ada Lovelace Award and the Computer Pioneer Award.

Sammet’s career started off in mathematics, and she turned over to programming in 1955. After she received the 2009 IEEE Computer Society Pioneer Award, she was asked about how she got involved in the computer field. She said: “In 1955, I was working at Sperry Gyroscope company on Long Island, and I was doing mathematical world involving submarines and torpedoes, and my boss came over to me one day and said ‘Do you know that we have a couple of engineers who are building digital computers?’ My answer was yes, I didn’t quite known what it meant but yes, and he said ‘Would you like to be our programmer’ and I said what is a programmer?’ and his answer, and I kid you not, his answer was ‘I don’t know but I know we need one.”

From there, she went on to teach computer programming classes at Adelphi, oversaw a team of developers for the U.S. Army’s Mobile Digital Computer for Sylvania, worked at IBM, organized the first Symposium on Symbolic and Algebraic Manipulation, became a member of the ACM Council, and became a fellow of the Computer History Museum (CHM).

“Jean Sammet was a leading figure in the study of computer programming languages. Her work has been widely recognized as an invaluable record of the origin and development of computer languages used since the start of the computing era,” CHM wrote.

More about her life is available here.

Sat, 04 Jun 2022 12:00:00 -0500 en-US text/html https://sdtimes.com/cobol/formac-developer-jean-sammet-died/
Killexams : Salon Joins With AdLedger and IBM to Trial a Blockchain Approach to Ad Tech Killexams : Salon Joins With AdLedger and IBM to Trial a Blockchain Approach to Ad Tech - Bitcoin Magazine - Bitcoin News, Articles and Expert Insights Skip to main content Sun, 07 Mar 2021 00:14:00 -0600 en text/html https://bitcoinmagazine.com/business/salon-joins-adledger-and-ibm-trial-blockchain-approach-ad-tech
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