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IBM invests in communities and helps shape programs that can deliver characteristics that matter to our clients and partners. We value open governance because it ensures the long-term success and viability of those projects that form the foundation of our enterprise offerings and solutions.
For example, IBM donated 44,000 lines of code to the Linux Foundation’s Hyperledger Project while providing new blockchain-as-a-service offerings on the IBM Cloud. IBM worked with other industry leaders in the Hyperledger Project because we recognize the long-term value of open collaboration and a cross-industry open standard for distributed ledgers.
We’re also investing in more and more open source from within IBM development and research labs.
IBM inventors received a record 9,100 patents in 2018,
This marks IBM’s 26th consecutive year of U.S. patent leadership. IBM led the industry in the number AI, cloud computing, security and quantum computing-related patent grants. "IBM is committed to leading the way on the technologies that change the way the world works – and solving problems many people have not even thought of yet," said Ginni Rometty, IBM chairman, president and CEO.
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Following University System of Georgia policy, UNG will use your Next Generation Accuplacer scores to determine placement into or out of Learning Support. Students who score below 243 on the studying test (scored on a 200-300 point scale) and/or below 4 on the WritePlacer (scored on a 0-8 point scale) will have a Learning Support English requirement at UNG. Students who score below 258 on the Quantitative Reasoning, Algebra, and Statistics (QRAS) test (scored on a 200-300 point scale) will have a Learning Support math requirement at UNG. Students scoring between 258 and 265 will have a Learning Support math requirement at UNG if their major requires College Algebra, MATH 1111, either as a core requirement or as a pre-requisite for a core math requirement. Your scores do not determine admissibility but, rather, determine placement. For more information about Learning Support you can read about it on the Learning Support Website.
If you have a red yes in any Placement Test Required row on your Check Application Status page in Banner, read the information below relating to the area in which you have the red yes.
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Today’s AI systems are quickly evolving to become humans’ new best friend. We now have AIs that can concoct award-winning whiskey, write poetry, and help doctors perform extremely precise surgical operations. But one thing they can’t do — which is, on the surface, far simpler than all those other things — is use common sense.
Common sense is different from intelligence in that it is usually something innate and natural to humans that helps them navigate daily life, and cannot really be taught. In 1906, philosopher G. K. Chesterton wrote that “common sense is a wild thing, savage, and beyond rules.”
Robots, of course, run on algorithms that are just that: rules.
So no, robots can’t use common sense — yet. But thanks to current efforts in the field, we can now measure an AI’s core psychological reasoning ability, bringing us one step closer.
Really it comes down to the fact that common sense will make AI better at helping us solve real-world issues. Many argue that AI-driven solutions designed for complex problems, like diagnosing Covid-19 treatments for example, often fail, as the system can’t readily adapt to a real-world situation where the problems are unpredictable, vague, and not defined by rules.
Common sense includes not only social abilities and reasoning but also a “naive sense of physics.”
Injecting common sense into AI could mean big things for humans; better customer service, where a robot can actually assist a disgruntled customer beyond sending them into an endless “Choose from the following options” loop. It can make autonomous cars react better to unexpected roadway incidences. It can even help the military draw life-or-death information from intelligence.
So why haven’t scientists been able to crack the common sense code thus far?
Called the “dark matter of AI”, common sense is both crucial to AI’s future development and, thus far, elusive. Equipping computers with common sense has actually been a goal of computer science since the field’s very start; in 1958, pioneering computer scientist John McCarthy published a paper titled “Programs with common sense” which looked at how logic could be used as a method of representing information in computer memory. But we’ve not moved much closer to making it a reality since.
Common sense includes not only social abilities and reasoning but also a “naive sense of physics” — this means that we know certain things about physics without having to work through physics equations, like why you shouldn’t put a bowling ball on a slanted surface. It also includes basic knowledge of abstract things like time and space, which lets us plan, estimate, and organize. “It’s knowledge that you ought to have,” says Michael Witbrock, AI researcher at the University of Auckland.
All this means that common sense is not one precise thing, and therefore cannot be easily defined by rules.
We’ve established that common sense requires a computer to infer things based on complex, real-world situations — something that comes easily to humans, and starts to form since infancy.
Computer scientists are making (slow) but steady progress toward building AI agents that can infer mental states, predict future actions, and work with humans. But in order to see how close we actually are, we first need a rigorous benchmark for evaluating an AI’s “common sense,” or its psychological reasoning ability.
Researchers from IBM, MIT, and Harvard have created just that: AGENT, which stands for Action-Goal-Efficiency-coNstraint-uTility. After testing and validation, this benchmark is shown to be able to evaluate the core psychological reasoning ability of an AI model. This means it can actually deliver a sense of social awareness and could interact with humans in real-world settings.
To demonstrate common sense, an AI model must have built-in representations of how humans plan.
So what is AGENT? AGENT is a large-scale dataset of 3D animations inspired by experiments that study cognitive development in kids. The animations depict someone interacting with different objects under different physical constraints. According to IBM:
“The videos comprise distinct trials, each of which includes one or more ‘familiarization’ videos of an agent’s typical behavior in a certain physical environment, paired with ‘test’ videos of the same agent’s behavior in a new environment, which are labeled as either ‘expected’ or ‘surprising,’ given the behavior of the agent in the corresponding familiarization videos.”
A model must then judge how surprising the agent’s behaviors in the ‘test’ videos are, based on the actions it learned in the ‘familiarization’ videos. Using the AGENT benchmark, that model is then validated against large-scale human-rating trials, where humans rated the ‘surprising’ ‘test’ videos as more surprising than the ‘expected’ test videos.
IBM’s trial shows that to demonstrate common sense, an AI model must have built-in representations of how humans plan. This means combining both a basic sense of physics and ‘cost-reward trade-offs’, which means an understanding of how humans take actions “based on utility, trading off the rewards of its goal against the costs of reaching it.”
While not yet perfect, the findings show AGENT is a promising diagnostic tool for developing and evaluating common sense in AI, something IBM is also working on. It also shows that we can utilize similar traditional developmental psychology methods to those used to teach human children how objects and ideas relate.
In the future, this could help significantly reduce the need for training in these models allowing businesses to save on computing energy, time, and money.
Robots don’t understand human consciousness yet — but with the development of benchmarking tools like AGENT, we’ll be able to measure how close we’re getting.
Tackle these vocabulary basics in a short practice test: synonyms and antonyms. Synonyms are words that have a similar meaning, and antonyms are words with opposite meanings. Students in first and second grade will think deeply about word meaning as they search for the matching synonym or antonym in each row of this studying and writing worksheet.
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The LSAT is a test of endurance under time pressure, like a mental marathon. It would be inadvisable to run…
The LSAT is a test of endurance under time pressure, like a mental marathon.
It would be inadvisable to run a marathon without first training to run a full 26.2 miles. Likewise, it’s a bad idea to take the LSAT without first training with real practice tests.
That said, very few athletes run daily marathons. Instead, they vary their training with shorter intervals and complementary forms of exercise. They might focus one day on sprinting or climbing hills and another day on strength and conditioning at the gym.
In the same way, LSAT test-takers should use full practice tests judiciously. Taking one test after another, day after day, may seem impressive, but it can reinforce bad habits and lead to burnout.
Improvement comes from focused and methodical practice with careful attention to review and experimentation. Still, real practice tests belong at the core of any LSAT study strategy, as long as they’re used well.
Accessing Real Practice LSAT Tests
Unlike other standardized tests, real LSAT tests are not hard to come by. In fact, the Law School Admission Council, which administers the exam, has made available more than 70 full, real, past LSAT tests for purchase, either through paperback compendiums of practice tests or through Official LSAT Prep Plus, which is currently priced at $99 and provides one year of access to an online bank of practice tests.
The LSAC also provides one free trial test online and five practice tests for members who sign up for an online account. Even more tests are available through private test prep companies.
Choosing a LSAT Practice Test
With so many tests available, where should law school applicants start? Since the mid-1990s, practice tests have been numbered in chronological order. More recent tests provide the most relevant practice.
The LSAT has changed a bit over time. In 2007, the studying comprehension section began including a comparative passage, and in 2019 the LSAT moved to a digital format. LSATs that date back to the 1990s may include less clear questions and more elaborate types of logic games than recent tests.
It’s also easier to find discussions and explanations of questions online for more recent LSATs.
That said, sections from old LSATs can be great substitutes for experimental sections. On the actual LSAT, one section will be experimental and unscored. Experimental sections often throw test-takers for a loop, precisely because they haven’t been correctly balanced and refined. Since older tests also feel a little offbeat, they achieve the same effect.
Using Timed and Untimed Practice
Taking full timed practice tests is great for simulating test conditions and getting a sense of your current LSAT score range. Most of the time, however, it is better to break each practice questions into individual sections. Taking each section at full attention, separated by downtime for rest and review while the questions are fresh in your memory, is more conducive to learning than taking a full test at once.
A good LSAT study plan should start with a period of mastering fundamental techniques learned from a book, course, online program or tutor.
Once you have the basics down, practice them by taking untimed sections. Work slowly and deliberately, as if you were learning how to swim or ski for the first time. The questions you get wrong with unlimited time are exactly the kinds of questions you should focus on in your practice and review.
It may come as a surprise, but you will pick up speed more reliably through untimed practice than through timed practice. Slowly working your way through difficult questions will help you break each question into a series of steps that eventually feel intuitive and automatic, like muscle memory. In contrast, time pressure makes it too tempting to cut corners.
Once you are performing consistently with untimed practice, move to timed section practice. Periodically take full practice tests, as a marathoner might space out long-distance runs.
Weeks of timed practice will help build stamina, so you can sustain the focus you need to perform at your best. By knowing exactly what you’re up against, you’ll face less test anxiety.
Following this plan will help make test day feel like just another day of practice — hopefully your last!
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Good news for programmers well-versed in the ways of the blockchain: IBM, Microsoft, USAA, and Visa are all searching for blockchain developers to join their teams right now, according to ads listed on their respective websites.
According to IBM's job listing, the company is seeking out “Consultant Developers” with experience on one or more blockchain platform, citing Ethereum, Hyperledger, and Ripple specifically, but also indicating that “equivalent proprietary platform experience” might also be considered. They are not particular about whether the developer has UX, backend, or full-stack experience.
Meanwhile, Microsoft is looking for a “Principal Program Manager." This person will “develop a deep understanding of how customers use distributed ledger technologies as well as compute, storage, database, and networking services in Azure to architect their applications.”
USAA is hoping to find a “Lead Blockchain Developer.” As for their “preferred qualifications,” the financial services company is hoping to find someone with at least two years experience with blockchain, cryptocurrencies, decentralized autonomous organizations, digital registries, distributed ledger, or smart contracts. Their ideal candidate will also have a conceptual knowledge of the mathematical foundations of blockchain technology.
Visa is searching for “a strong developer experienced with Ethereum and blockchain architecture.” As for specifics, they want someone who "has built and released distributed applications, has worked with the Ripple, R3, Ethereum, and/or Bitcoin blockchain, and has experience with Solidity.” Visa also notes that their candidate will need to “maintain [the company's] relationship with the [IBM] Hyperledger initiative.”
The interest in developers with blockchain experience is just one more sign that the technology is poised to radically transform our world. Notably, both USAA and Visa are looking for developers with Ethereum experience — no surprise given the strong presence the blockchain now has among financial companies, many of which are using Ethereum as the basis for their blockchain technologies.
IBM and Microsoft are already well on their way to integrating the blockchain into their business models. PC Mag reports that both have custom blockchains for their own blockchain-as-a-service (BaaS) platforms (Bluemix for IBM and Azure for Microsoft) using their cloud infrastructure. These platforms allow the companies to experiment with use cases for customers and for their own purposes.
At the heart of IBM's short-term goals is blockchain identity management — a real-world, ultra-secure applied use of the technology to guard identity and associated financial and other sensitive information online — so if you're thinking about applying there, chances are excellent you'll be working on something related to that.
Whether they land at IBM or one of the several other companies looking to delve deeper into blockchain, the developers who fill these open positions will be the people ushering in an entirely new era in technology.
Disclosure: Several members of the Futurism team, including the editors of this piece, are personal investors in a number of cryptocurrency markets. Their personal investment perspectives have no impact on editorial content.
Global tech major IBM, which employs over one lakh individuals in India, on Wednesday termed moonlighting an unethical practice.
Moonlighting, the practice of taking up secondary jobs after regular work hours, has recently been highlighted by many tech companies.
IBM's managing director for India and South Asia, Sandip Patel said, at the time of joining, employees sign an agreement saying they will be working only for IBM.
“…notwithstanding what people can do in the rest of their time, it is not ethically right to do that (moonlighting),” Patel told reporters on the sidelines of a company event.
Tech players in India are expressing varied opinions on moonlighting or side hustles, where an employee undertakes some other work for extra income.
Wipro's Chairman Rishad Premji had termed such behaviour by employees “cheating”.
“I share Rishad's position,” Patel said.
When asked about the company's hiring plans for India, which holds a key role as a talent base and as a market for the company, Patel said migration of employees to their hometowns during the pandemic has not completely reversed and hence, the IT industry has adopted the hybrid model of working.
Calling tier-2 and tier-3 cities as “emerging clusters”, Patel said the company has plans of deepening its presence in the country.
The company also announced that it has signed up with Airtel to offer its secured edge cloud services to the telco.
The Airtel platform backed by IBM cloud satellite will power Maruti Suzuki's initiatives to streamline play productivity and quality operations, a statement by IBM said.
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