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Killexams : IBM Intelligence course outline - BingNews Search results Killexams : IBM Intelligence course outline - BingNews Killexams : Search IBM Courses No result found, try new keyword!Search for courses ... intelligence, built chatbots and have perhaps even used Watson Assistant along the way. But did you know that you can turbocharge your chatbot's IQ with IBM Watson Discovery ... Thu, 22 Apr 2021 07:23:00 -0500 text/html Killexams : IBM Just Committed $240 Million to the Future of Artificial Intelligence


IBM is officially partnering with the Massachusetts Institute of Technology (MIT) to run an artificial intelligence (AI) research lab. This Watson-branded joint MIT-IBM AI research initiative — a partnership of acronyms — will be funded through a 10-year, $240 million investment from IBM and will be co-located at IBM's Research Lab in Cambridge and at the MIT campus.

Click to View Full Infographic

According to an IBM press release, the MIT-IBM Watson AI Lab will be one the largest long-term AI collaborations between a university and a member of the tech industry.

Its goal is to enable more than 100 scientists, professors, and students to pursue research focused on such areas as the development of AI algorithms that could expand machine learning capabilities, the improvement of AI hardware, the exploration of AI's economic and societal benefits, and the identification of AI applications in key industries.

Much-Needed Help

The team at IBM knows that despite all the recent attention given to what AI can do, there's still so much that it can't.

“The field of artificial intelligence has experienced incredible growth and progress over the past decade," IBM's senior VP for Cognitive Solutions and Research John Kelly III said in the press release. "Yet today’s AI systems, as remarkable as they are, will require new innovations to tackle increasingly difficult real-world problems to Boost our work and lives."

IBM and MIT want to work together on those innovations, and their partnership might be exactly what's needed to put AI's promise to use in the real world. IBM has already illustrated the potential for their Watson AI to Boost healthcare, and with MIT's help, they may be able to take the technology even further in that field and so many others.

“True breakthroughs are often the result of fresh thinking inspired by new kinds of research teams," asserted MIT President L. Rafael Reif in the IBM press release. "The combined MIT and IBM talent dedicated to this new effort will bring formidable power to a field with staggering potential to advance knowledge and help solve important challenges.”

Thu, 07 Sep 2017 05:14:00 -0500 text/html
Killexams : International Business Machines Corp

52 week range

114.56 - 144.73

  • Open0.00
  • Day High0.00
  • Day Low0.00
  • Prev Close120.04
  • 52 Week High144.73
  • 52 Week High Date06/06/22
  • 52 Week Low114.56
  • 52 Week Low Date11/26/21
  • Market Cap108.418B
  • Shares Out903.18M
  • 10 Day Average Volume4.62M
  • Dividend6.60
  • Dividend Yield5.50%
  • Beta0.83
  • YTD % Change-10.19


  • Open0.00
  • Day High0.00
  • Day Low0.00
  • Prev Close120.04
  • 52 Week High144.73
  • 52 Week High Date06/06/22
  • 52 Week Low114.56
  • 52 Week Low Date11/26/21
  • Market Cap108.418B
  • Shares Out903.18M
  • 10 Day Average Volume4.62M
  • Dividend6.60
  • Dividend Yield5.50%
  • Beta0.83
  • YTD % Change-10.19


  • EPS (TTM)6.42
  • P/E (TTM)18.69
  • Fwd P/E (NTM)12.31
  • EBITDA (TTM)11.935B
  • ROE (TTM)27.73%
  • Revenue (TTM)59.677B
  • Gross Margin (TTM)54.01%
  • Net Margin (TTM)9.61%
  • Debt To Equity (MRQ)259.21%


  • Earnings Date10/19/2022
  • Ex Div Date08/09/2022
  • Div Amount1.65
  • Split Date-
  • Split Factor-

Thu, 13 Oct 2022 11:59:00 -0500 en text/html
Killexams : IBM integrates business intelligence and data science with new major update to Cognos Analytics

More enterprises are on a quest to use artificial intelligence as a competitive advantage. IBM is on a mission to make this easier and more accessible for any organization via the cloud. The company has announced a new version of its Cognos Analytics solution, which integrates business intelligence and data science technologies into a suite of tools available on IBM Cloud.

The key new features of this release are a new AI Assistant and pattern detection capability. The AI Assistant enables users to make queries and then receive results in natural language. According to IBM, this makes it easier to not only look for answers, but understand where they come in.

Pattern detection identifies and presents critical relationships within data, pointing out patterns that may not have been considered previously. By detecting patterns, the system can eliminate blind spots or guesswork in analysis, the company explained.

“When combined with the foundational governance and trust capabilities built into Cognos Analytics, which provide data policy, relevancy, integrity and security, AI Assistant and pattern detection will give users not only fast access to insights, but added confidence in the results,” Greg Adams, vice president of development for business analytics at IBM, wrote in a post.

This version also adds storytelling, which allows users to create interactive narratives by assembling visualizations into a sequence and then enhancing it with media, web pages, images, shapes, and test.

Smart exploration will help users be able to better understand what’s behind their results by analyzing it with machine learning and pattern detection. The system will also recommend the most useful visualization of results through a multi-stage recommendation system.

The system assembles new content quickly by re-using relevant components from existing dashboards.

Finally, it has advanced analytics that include predictive analytics, the ability to identify data patterns and variables driving a certain outcome, smart annotation, and natural language generated insights of data.

“Analytics, data science and business intelligence, have become table stakes in the business world,” wrote Adams. “They’re part of the fundamental building blocks, or rungs in the Ladder to AI, as we talk about. And we’ve worked hard to make these sophisticated, complicated technologies easy to access, easy to use, and easy to comprehend for just about any – all via the IBM Cloud. We think organizations the world over will see real value in it and begin making even better, more strategic decisions to propel their businesses into the future.”

Mon, 26 Sep 2022 11:59:00 -0500 en-US text/html
Killexams : Artificial Intelligence (AI) in Insurance Market May See a Big Move : Google, Microsoft , IBM: Long Term Growth Story

New Jersey, NJ -- (SBWIRE) -- 10/10/2022 -- The Global Artificial Intelligence (AI) in Insurance Market Report assesses developments relevant to the insurance industry and identifies key risks and vulnerabilities for the Artificial Intelligence (AI) in Insurance Industry to make stakeholders aware with current and future scenarios. To derive complete assessment and market estimates a wide list of Insurers, aggregators, agency were considered in the coverage; Some of the top players profiled are Google, Microsoft Corporation, Amazon Web Services Inc, IBM Corporation, Avaamo Inc, Baidu Inc, Cape Analytics LLC, Oracle Corporation & ?Artificial Intelligence (AI) in InsuranceMarket Scope and Market Breakdown.

Next step one should take to boost topline? Track recent strategic moves and product landscape of Artificial Intelligence (AI) in Insurance market.

Get Free Access of Global Artificial Intelligence (AI) in Insurance Market Research sample PDF

Globally, the insurance industry experienced strong premium growth in 2022, at percent, whereas growth in 2022 is noticeably slower, at percent. Total premiums (GWP) are expected to reach ... by 2028. Artificial Intelligence (AI) in Insurance Companies seeking top growth opportunities in the global insurance markets can explore both the fastest-growing markets and the largest developed markets; the slowing growth rates suggest; however, most carriers would also need to search farther afield. "The growth during this period will be fuelled by the emerging markets in the APAC and Latin American regions"

The report depicts the total market of Artificial Intelligence (AI) in Insurance industry; further market is broken down by application [on, Life Insurance, Car Insurance, Property Insurance, Channel, By Channels, Market has been segmented into, Direct Sales, Distribution Channel, Regional & Country Analysis, North America Country (United States, Canada), South America (Brazil, Argentina, Peru, Chile, Rest of South America), Asia-Pacific (China, Japan, India, South Korea, Australia, Singapore, Malaysia, Indonesia, Philippines, Thailand, Vietnam, Others), Europe (Germany, United Kingdom, France, Italy, Spain, Switzerland, Netherlands, Austria, Sweden, Norway, Belgium, Rest of Europe) & Rest of World [GCC, South Africa, Egypt, Turkey, Israel, Others]], type [, Software & Platform] and country.

Geographically, the global version of report covers following regions and country:
- North America [United States, Canada and Mexico]
- Europe [Germany, the UK, France, Italy, Netherlands, Belgium, Russia, Spain, Sweden, and Rest of Europe]
- Asia-Pacific [China, Japan, South Korea, India, Australia, Southeast Asia and Others]
- South America [Brazil, Argentina, Chile and Rest of South America]
- Middle East and Africa (South Africa, Turkey, Israel, GCC Countries and Rest of Africa)

Browse Executive Summary and Complete Table of Content @

Research Approach & Assumptions:

- HTF MI describe major trends of Global Artificial Intelligence (AI) in Insurance Market using final data for 2022 and previous years, as well as quarterly or annual reports for 2022. In general, Years considered in the study i.e. base year as 2022, Historical data considered as 2022-2028and Forecast time frame is 2022-2028.

- Various analytical tools were used to assess how the insurance Sector and particularly Artificial Intelligence (AI) in Insurance Industry might respond over the next decade to global macroeconomic shifts. Our "consensus scenario" assumes a recovery of Global GDP growth in the coming years in addition to fluctuating interest rates; the results presented in Artificial Intelligence (AI) in Insurance Market report reflect the output of this model.

- While calculating growth of Artificial Intelligence (AI) in Insurance Market, we generally used nominal gross premium figures based on 2022 fixed exchange rates, since this data allowed us to compare local growth rates without the interference of currency fluctuations. The exceptions, which use floating exchange rates, are Argentina, Ukraine, and Venezuela, many African Countries etc due to high inflation rates.

Get full access to Global Artificial Intelligence (AI) in Insurance Market Report; Buy Latest Edition Now @:

Thanks for practicing Artificial Intelligence (AI) in Insurance Industry research publication; you can also get individual chapter wise section or region wise report version like USA, China, Southeast Asia, LATAM, APAC etc.

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HTF Market Intelligence consulting is uniquely positioned empower and inspire with research and consulting services to empower businesses with growth strategies, by offering services with extraordinary depth and breadth of thought leadership, research, tools, events and experience that assist in decision making.

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Mon, 10 Oct 2022 09:21:00 -0500 en-US text/html
Killexams : Artificial Intelligence in Energy Market Market Still Has Room to Grow | Siemens, Schneider Electric, IBM, General Electric

The latest study released on the Global Artificial Intelligence in Energy Market by AMA Research evaluates market size, trend, and forecast to 2027. The Artificial Intelligence in Energy market study covers significant research data and proofs to be a handy resource document for managers, analysts, industry experts and other key people to have ready-to-access and self-analyzed study to help understand market trends, growth drivers, opportunities and upcoming challenges and about the competitors.

Download sample Report PDF (Including Full TOC, Table & Figures) @

Key Players in This Report Include:

Alphabet (United States), General Electric (United States), Siemens (Germany), Watty (Sweden), IBM (United States), Schneider Electric (France), BuildingIQ (United States), ABB (Switzerland), Grid4C (United States)


Artificial intelligence in the energy sector is now reaching emerging markets, where it may have a critical impact, as clean, cheap, and reliable energy is essential to development. Artificial intelligence technologies are closely tied to the ability to provide clean and cheap energy that is essential to development. Increasing demand for artificial intelligence in the energy sector from developed nations that allow for communication between smart grids, smart meters, and Internet of Things devices is propelling the growth of the global artificial intelligence in the energy market.

Market Trends:
Increasing Use of Machine Learning

Market Drivers:
Lack of Analytics Needed for Optimal Management
Rising Demand for Energy across the Globe

Market Opportunities:
Technological Advancement and Development in Artificial Intelligence in Energy

The Global Artificial Intelligence in Energy Market segments and Market Data Break Down are illuminated below:

by Type (Software, Hardware, Services), Application (Fault Prediction, Maintenance Facilitated by Image Processing, Energy Efficiency Decision Making, Disaster Recovery, Prevention of Losses Due to Informal Connections), Organization Size (Small and Medium Size Organization, Large Size Organization), Deployment (Cloud-based, On-premise)

Global Artificial Intelligence in Energy market report highlights information regarding the current and future industry trends, growth patterns, as well as it offers business strategies to helps the stakeholders in making sound decisions that may help to ensure the profit trajectory over the forecast years.

Have a query? Market an enquiry before purchase @

Geographically, the detailed analysis of consumption, revenue, market share, and growth rate of the following regions:

The Middle East and Africa (South Africa, Saudi Arabia, UAE, Israel, Egypt, etc.)

North America (United States, Mexico & Canada)

South America (Brazil, Venezuela, Argentina, Ecuador, Peru, Colombia, etc.)

Europe (Turkey, Spain, Turkey, Netherlands Denmark, Belgium, Switzerland, Germany, Russia UK, Italy, France, etc.)

Asia-Pacific (Taiwan, Hong Kong, Singapore, Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia).

Objectives of the Report:

-To carefully analyze and forecast the size of the Artificial Intelligence in Energy market by value and volume.

-To estimate the market shares of major segments of the Artificial Intelligence in Energy

-To showcase the development of the Artificial Intelligence in Energy market in different parts of the world.

-To analyze and study micro-markets in terms of their contributions to the Artificial Intelligence in Energy market, their prospects, and individual growth trends.

-To offer precise and useful details about factors affecting the growth of the Artificial Intelligence in Energy

-To provide a meticulous assessment of crucial business strategies used by leading companies operating in the Artificial Intelligence in Energy market, which include research and development, collaborations, agreements, partnerships, acquisitions, mergers, new developments, and product launches.

Buy Complete Assessment of Artificial Intelligence in Energy market Now @

Major highlights from Table of Contents:

Artificial Intelligence in Energy Market Study Coverage:

It includes major manufacturers, emerging player’s growth story, and major business segments of Artificial Intelligence in Energy market, years considered, and research objectives. Additionally, segmentation on the basis of the type of product, application, and technology.

Artificial Intelligence in Energy Market Executive Summary: It gives a summary of overall studies, growth rate, available market, competitive landscape, market drivers, trends, and issues, and macroscopic indicators.

Artificial Intelligence in Energy Market Production by Region Artificial Intelligence in Energy Market Profile of Manufacturers-players are studied on the basis of SWOT, their products, production, value, financials, and other vital factors.

Key Points Covered in Artificial Intelligence in Energy Market Report:

Artificial Intelligence in Energy Overview, Definition and Classification Market drivers and barriers

Artificial Intelligence in Energy Market Competition by Manufacturers

Impact Analysis of COVID-19 on Artificial Intelligence in Energy Market

Artificial Intelligence in Energy Capacity, Production, Revenue (Value) by Region (2022-2027)

Artificial Intelligence in Energy Supply (Production), Consumption, Export, Import by Region (2022-2027)

Artificial Intelligence in Energy Manufacturers Profiles/Analysis Artificial Intelligence in Energy  Manufacturing Cost Analysis, Industrial/Supply Chain Analysis, Sourcing Strategy and Downstream Buyers, Marketing

Strategy by Key Manufacturers/Players, Connected Distributors/Traders Standardization, Regulatory and collaborative initiatives, Industry road map and value chain Market Effect Factors Analysis.

Browse Complete Summary and Table of Content @

Key questions answered:

How feasible is Artificial Intelligence in Energy market for long-term investment?

What are influencing factors driving the demand for Artificial Intelligence in Energy near future?

What is the impact analysis of various factors in the Global Artificial Intelligence in Energy market growth?

What are the recent trends in the regional market and how successful they are?

Thanks for practicing this article; you can also get individual chapter wise section or region wise report version like North America, Middle East, Africa, Europe or LATAM, Southeast Asia.

Contact US :

Craig Francis (PR & Marketing Manager)

AMA Research & Media LLP

Unit No. 429, Parsonage Road Edison, NJ

New Jersey USA – 08837

Phone: +1 (551) 333 1547

[email protected]

Tue, 04 Oct 2022 02:00:00 -0500 Newsmantraa en-US text/html
Killexams : Artificial Intelligence Identifies IBM And Netflix Among Trending Stocks This Week

Last week, our trending stock lists collected a motley crew of companies ranging from biotech to regular tech to home entertainment tech. In general, there was just a lot of tech.

For the week of May 16, many of those same stocks hit our trending roundup again – for good reason. From a 49 million square foot downgrade to a pilot program intended to put credit cards in the hands of the credit-less, here’s an inside look at what’s making the market pop. runs daily factor models to get the most up-to-date practicing on stocks and ETFs. Our deep-learning algorithms use Artificial Intelligence (AI) technology to provide an in-depth, intelligence-based look at a company – so you don’t have to do the digging yourself.

Sign up for the free Forbes AI Investor newsletter here to join an exclusive AI investing community and get premium investing ideas before markets open.

International Business Machines Corporation (IBM)

First up in our weekly trending list is International Business Machines, which closed up 0.35% on Friday to $144.68 with 2.7 million trades on the books. The stock is up almost 15% for the year.

IBM a repeat customer from last week, after announcing the week before that they had developed the world’s first 2nm chip-making technology. Now, IBM is trending, likely in part due to a slew of messages surrounding the future of the company’s working arrangements.

CEO Arvind Krishna declared last week that IBM expects up to 80% of its 350,000 employees to opt for a hybrid office-remote work arrangement, with the remaining 20% keeping their position as fully remote employees. And while he cautioned that “nobody should make firm plans for another two or three months,” he also acknowledged that these arrangements will vary around the world to account for individual countries’ situations regarding the pandemic.

In anticipation of this massive workplace shift, IBM is planning to shed “tens of millions” of square feet of real estate. The company plans to move to the CrossPoint office complex in Lowell, Massachusetts, downsizing from almost 50 million square feet to a mere 150,608.

The downgrade will likely help IBM’s bottom line as well as their employee working conditions – something the company has surely considered. Although an operating income of $8.58 billion in the last fiscal year doesn’t exactly put the company in “hurting” territory, this is a touch over half of their $13.2 billion operating income three years ago.

Plus, their mere 0.21% in revenue growth to $73.6 billion isn’t quite up to snuff compared to their three-year-ago revenue of nearly $79.6 billion. Their EPS has fallen in the same timeframe, too, from $9.52 to $6.23, while their ROE has decline from 50.3% to 26.4%.

Still, when you’re down, there’s nowhere to go but up: the company is expected to see revenue growth of 0.57% in the next twelve months. And with a forward 12-month P/E of 12.8x, their stock shows plenty of room for growth, as well.

Our AI sees IBM as having above-average potential overall, as well, though it could be doing better in some areas. The company earned C’s in Technicals and Growth, and B’s in Quality Value and Low Volatility Momentum, setting them up for an optimistic future.

Netflix, Inc (NFLX)

Netflix NFLX  is a company that needs no introduction – especially seeing as how it, too, appeared on last week’s trending lists. The streaming media giant remains a household name due to its invaluable services during the pandemic – and a stock staple due to its overall history of turning out profits.

Although Netflix fell short 2 million subscribers in its most recent earnings report, it still closed up almost 1.4% on Friday to $493.37 per share, ending the week on a positive note with 2.88 million trades in the bank. Still, its stock remains down 8.8% YTD.

Netflix’s high stock prices are mostly supported by its underlying performance – revenue grew almost 5.6% in the last fiscal year and 67% in the last three, bringing total revenue to $25 billion. Of this, the company netted $4.585 billion in operating income, almost triple their $1.6 billion operating income three years ago. And their EPS has risen 35.9% in the last year alone and 208% in the last three, seeing per-share earnings grow from $2.68 to $6.08.

And while you might think that a company this big has nowhere to go, you’d be wrong: Netflix’s revenue is expected to expand 3.33% in the next twelve months. At the same time, some analysts see the stock as overvalued (largely due to the inability to monetize their Netflix Originals via traditional methods), and their forward 12-month P/E of 47.53 appears to support this claim.

Still, our AI doubts that Netflix has reached its cap; far from it. In fact, Netflix earned an A in Growth, with B’s in Low Volatility Momentum and Quality Value – though it did net a D in Technicals. Only time will tell if Netflix is able to grow as pandemic restrictions loosen at last and the broader economy reopens.

Moderna, Inc (MRNA)

Last week was a roller coaster week for vaccine manufacturers after the Biden administration openly supported an initiative to waive Covid-19 vaccine patents in order to bolster global production. This announcement – as well as Moderna’s MRNA announcement that it would funnel at least 34 million doses to struggling countries – saw the stock trend twice last week.

Once again, Moderna makes our list of trending stocks as shares closed up 7.7% on Friday to $161.38 on volume of 6.5 million trades. While the stock has been falling over the past month, as indicated in the 22-day price average of $167 and change, the stock is still up almost 54.5% YTD.

Moderna can once again thank the government for its upward trend, as shares of the biotech company rose after an announcement from the CDC that individuals who are fully vaccinated can “participate in indoor and outdoor activities, large or small, without wearing a mask or physical distancing.” While Moderna can’t claim full credit, distributing hundreds of millions of doses of their mRNA vaccine surely helped make this long-awaited declaration possible.

And in further good news, Australia last week noted that it’s in talks with Moderna to establish domestic production of messenger RNA vaccines. The company is also supposedly conferring with Samsung BioLogics Co Ltd to start production of the Moderna vaccine in South Korea (though no official decision has been made) after two expert panels recommended that Moderna’s vaccine be approved for emergency use.

Moderna is one of those fortunate companies that benefitted from the pandemic more than it was hurt, as the biotech company saw their revenue expand 240% in the last fiscal year to $803 million, compared to $135 million three years ago. Their operating income almost doubled in the same time frame, from $413 million to $763 million, though per-share earnings plummeted from $4.95 to $1.96.

Moderna is expected to see revenue growth of 16.2% over the next twelve months. And with a forward-facing P/E of 5.84x, there’s some indication that the company may be undervalued.

However, our AI is wary of Moderna – especially after a year of such rapid, and situation-specific, growth. The company scored its highest rating, B, in Growth, with D’s across the rest of the board in Technicals, Quality Value, and Low Volatility Momentum.

Intel Corporation (INTL)

After making our trending list last week after Atlantic Equities downgraded the chipmaker to underweight, Intel INTC is back after closing up almost 2.5% to $55.35 on Friday with 28 million trades on the books. Though the stock has seen some losses in the last 10 days, it’s still up 11% YTD.

Intel’s struggles in chip manufacturing and delivery have been compounded in recent weeks during the global chip shortage, with the company still behind several nanometers in design – not to mention grappling with the results of a $2.2 billion judgment by a federal jury in March over patent infringement. Still, the company managed to deliver strong Q1 results in April, driven by exceptional product demand.

However, Intel’s last year was not its best – its numbers are roughly stagnant in the three-year timespan. Revenue is up 9.7% over the past three years, from $70.8 billion to $77.9 billion, though operating income barely ticked up from $23.2 billion to $23.9 billion. Its EPS has risen by around $0.50 to $4.94 in per-share earnings, with ROE down to 26% from 29%. All in all, Intel is trading with a forward 12-month P/E of 12.94x.

Our AI doesn’t have much faith in Intel to turn its situation around anytime soon, either. The company earned below-average ratings across the board from our artificial intelligence, with C’s in Quality Value and Low Volatility Momentum, D in Growth, and F in Technicals.

Wells Fargo & Company (WFC)

Wells Fargo WFC closed up 1.2% on Friday to $46.96 on volume of 17 million trades. The company is up 55.6% YTD, despite waffling between $46 and $45 on its 10- and 22-day price averages.

Wells Fargo has been on a massive public rehabilitation campaign since 2018, wading through scandal after lawsuit due to deplorable business practices that damaged the credit of their members and tarnished their reputation (and bottom line). In the years since, despite some slip-ups, Wells Fargo has done their best to make a comeback – and with their stock earnings approaching pre-pandemic numbers at last, the company may just be about to make it.

Later this year, Wells Fargo is set to join a number of companies – including fellow financial giants US Bancorp USB and JPMorgan Chase JPM – in a government-backed pilot program to put credit cards in the hands of credit invisible individuals. Under this program, banks will share applicant information regarding balances and overdraft histories to identify financially responsible individuals who haven’t previously built credit. If the initiative proves promising, the banks may move into other types of lending – particularly auto loans – for responsible credit invisible individuals, as well.

This program gives Wells Fargo – a company that once hurt the credit of thousands of its members – a chance to redeem itself and give members a financial foot forward. That’s something that the company has experienced itself in the last year, as the company saw a revenue increase of 9.3% to $58.3 billion (down from $84.7 billion three years ago), and operating income growth of 216% to $2.1 billion (down from $28.5 billion three years ago).

And while its EPS and ROE remain in the tank - $0.41 and 1.92%, respectively – Wells Fargo maintains a forward 12-month P/E of 14.16x.

Still, our AI remains skeptical of Wells Fargo, rating the company just below average with a D in Quality Value and C’s in Technicals, Growth, and Low Volatility Momentum.

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Mon, 17 May 2021 05:47:00 -0500 - Powering a Personal Wealth Movement en text/html
Killexams : IBM Bids Farewell to Watson Health Assets

IBM shook up the digital health space Friday with the news that it is selling its healthcare data and analytics assets, currently part of the Watson Health business, to an investment firm. The sale price is reportedly more than $1 billion, although the companies are not officially disclosing the financial terms.

There are a lot of interesting factors to consider as we unpack this news, although some thought leaders say the divestiture did not come as a surprise.

“The Watson Health sale has been anticipated for quite some time. IBM was clearly not gaining much traction in the healthcare market while others such as Google and Microsoft have pulled ahead. Even Oracle has made a big splash in healthcare with its recent announcement to acquire Cerner," said Paddy Padmanabhan, founder and CEO of Damo Consulting, a growth strategy and digital transformation advisory firm that works with healthcare and technology companies.

IBM was one of the first big tech companies to dive into healthcare with its well-known Watson Health supercomputer known for defeating the greatest champions on “Jeopardy!" The platform created a lot of buzz back in 2011, and many people had high hopes for the platform's potential applications in healthcare. In recent years, however, that buzz has significantly died down.

"In the current competitive landscape, IBM would not be considered a significant player in healthcare. Selling off the data assets essentially means an end to the Watson Health experiment; however, it may allow IBM as an organization to refocus and develop a new approach to healthcare,” Padmanabhan said.

Assuming there are no regulatory snags, the deal is expected to close in the second quarter of this year.

“Today’s agreement with Francisco Partners is a clear next step as IBM becomes even more focused on our platform-based hybrid cloud and AI strategy,” said Tom Rosamilia, senior vice president of IBM Software. “IBM remains committed to Watson, our broader AI business, and to the clients and partners we support in healthcare IT. Through this transaction, Francisco Partners acquires data and analytics assets that will benefit from the enhanced investment and expertise of a healthcare industry focused portfolio.”

The agreement calls for the current management team to continue in similar roles in the new standalone company, serving existing clients in life sciences, provider, imaging, payer and employer, and government health and human services sectors.

“We have followed IBM’s journey in healthcare data and analytics for a number of years and have a deep appreciation for its portfolio of innovative healthcare products,” said Ezra Perlman, co-president at Francisco Partners. “IBM built a market-leading team and provides its customers with mission critical products and outstanding service.”

In 2016 IBM doubled the size of its Watson Health business through the $2.6 billion acquisition of Truven Health Analytics. Truven offers healthcare data services targeted at employers, hospitals, and drug companies, and makes software that can parse through millions of patient records. Truven's main offices are in Ann Arbor, MI, Chicago, and Denver. At the time of the acquisition, Truven had around 2,500 employees.

The Truven deal followed other major healthcare acquisitions in the company, including Cleveland-based Explorys, Dallas-based Phytel, and Chicago-based Merge Healthcare. The company paid about $1 billion for Merge.

IBM said the assets acquired by Francisco Partners include extensive and diverse data sets and products, including Health Insights, MarketScan, Clinical Development, Social Program Management, Micromedex, and imaging software offerings.

Padmanabhan said it will be interesting to see how the new owners are able to leverage those data assets.

“IBM’s decision to sell its data assets is an indication that it’s not just enough to have the data. Applying advanced analytics on the data to generate insights that can make a difference in real-world applications is where the true value lies. IBM had several missteps early on, especially in cancer care applications, that created significant setbacks for the business that they could not recover from.

In 2018, the Watson Health business went through a round of layoffs. The company declined to tell MD+DI at the time how many of employees were let go other than to say it was a "small percentage" of the global business, but online commenters on and Watching IBM, along with multiple news reports citing unnamed sources from within the organization painted a different picture of the situation. One Dallas-based commenter on said that "we all knew it was coming but nobody expected it to be this fast and rampant," while another commenter estimated that 80% of that same Dallas-based office was let go.

Is healthcare just too hard for big tech?

While we have seen a trend in recent years with big tech firms showing an interest in healthcare, some of those companies are finding those efforts to be easier said than done. 
“IBM’s decision to sell the Watson Health assets is another instance of a big tech firm acknowledging the challenges of the healthcare space. Last year, Google and Apple had significant setbacks, and Amazon has acknowledged challenges in scaling its Amazon Care business," Padmanabhan said. "In IBM’s case, they have missed out on the cloud opportunity and have lagged behind peers in emerging technology areas such as voice. While IBM’s challenges with Watson Health may have been unique to the organization, the fact is that big tech firms have multiple irons in the fire at any time, and for some healthcare may just be too hard.”

Padmanabhan does not think, however, that IBM's decision to sell the Watson Health assets is an indictment of the promise of AI in healthcare.

"Our research indicates AI was one of the top technology investments for health systems in 2021," he said. "Sure, there are challenges such as data quality and bias in the application of AI in the healthcare context, but by and large there has been progress with AI in healthcare. The emergence of other players, notably Google with its Mayo Partnership, or Microsoft with its partnership with healthcare industry consortium Truveta are strong indicators of progress."
Padmanabhan is co-author with Edward W. Marx, of Healthcare Digital Transformation: How Consumerism, Technology and Pandemic are Accelerating the Future (2020), and the host of The Big Unlock, a podcast focusing on healthcare digital transformation.

Wed, 12 Oct 2022 12:00:00 -0500 en text/html
Killexams : This year’s physics Nobel Prize went to pioneers in quantum tech. Here’s how their work could change the world.

Quantum computing is one of those technologies of the future — like nuclear fusion power or self-driving cars — that seems as potentially transformative as it is perpetually just out of reach. If researchers are able to develop quantum machines that are stable and reliable, it could jump-start the pace of computing, which has slowed down as Moore’s Law — the long-accurate prediction by Intel co-founder Gordon Moore that computer chips would get faster and cheaper — seems to be coming to an end. But the path to a practical quantum computer has been long and difficult, combining some of the hardest problems in quantum science with the hardest problems in computing hardware.

Just how long the road to quantum computing has been — and how important it will be to reach the destination — became clear again on Tuesday morning when the Nobel Prize in physics for 2022 was awarded to three researchers whose work had “laid the foundation for a new era of quantum technology,” as the Nobel Committee on Physics put it.

John F. Clauser, an American, showed in 1972 that photon pairs were entangled, underscoring that the particles behave like a single unit even when separated by great distances. Alain Aspect of the University of Paris furthered that work a decade later, and in 1998, Austrian physicist Anton Zeilinger explored entanglement for three or more particles. Together, as the Nobel Committee put it, they paved the way for “new technology based upon quantum information.”

But a real, workable quantum computer will take much more than theory, as I learned on a visit earlier this year to the small Westchester County community of Yorktown Heights. There, amid the rolling hills and old farmhouses, sits the Thomas J. Watson Research Center, the Eero Saarinen-designed, 1960s Jet Age-era headquarters for IBM Research.

Deep inside that building, through endless corridors and security gates guarded by iris scanners, is where the company’s scientists are hard at work developing what IBM director of research Dario Gil told me is “the next branch of computing”: quantum computers.

I was at the Watson Center to preview IBM’s updated technical roadmap for achieving large-scale, practical quantum computing. This involved a great deal of talk about “qubit count,” “quantum coherence,” “error mitigation,” “software orchestration” and other syllabus you’d need to be an electrical engineer with a background in computer science and a familiarity with quantum mechanics to fully follow.

I am not any of those things, but I have watched the quantum computing space long enough to know that the work being done here by IBM researchers — along with their competitors at companies like Google and Microsoft, along with countless startups around the world — stands to drive the next great leap in computing. Which, given that computing is a “horizontal technology that touches everything,” as Gil told me, will have major implications for progress in everything from cybersecurity to artificial intelligence to designing better batteries.

Provided, of course, they can actually make these things work.

Entering the quantum realm

The best way to understand a quantum computer — short of setting aside several years for grad school at MIT or Caltech — is to compare it to the kind of machine I’m typing this piece on: a classical computer.

My MacBook Air runs on an M1 chip, which is packed with 16 billion transistors. Each of those transistors can represent either the “1” or “0” of binary information at a single time — a bit. The sheer number of transistors is what gives the machine its computing power.

Sixteen billion transistors packed onto a 120.5 sq. mm chip is a lot — TRADIC, the first transistorized computer, had fewer than 800. The semiconductor industry’s ability to engineer ever more transistors onto a chip, a trend forecast by Intel co-founder Gordon Moore in the law that bears his name, is what has made possible the exponential growth of computing power, which in turn has made possible pretty much everything else.

The exterior of an IBM System One quantum computer, as seen at the Thomas J. Watson Research Center.
Bryan Walsh/Vox

But there are things classic computers can’t do that they’ll never be able to do, no matter how many transistors get stuffed onto a square of silicon in a Taiwan semiconductor fabrication plant (or “fab,” in industry lingo). And that’s where the unique and frankly weird properties of quantum computers come in.

Instead of bits, quantum computers process information using qubits, which can represent “0” and “1” simultaneously. How do they do that? You’re straining my level of expertise here, but essentially qubits make use of the quantum mechanical phenomenon known as “superposition,” whereby the properties of some subatomic particles are not defined until they’re measured. Think of Schrödinger’s cat, simultaneously dead and alive until you open its box.

A single qubit is cute, but things get really exciting when you start adding more. Classic computing power increases linearly with the addition of each transistor, but a quantum computer’s power increases exponentially with the addition of each new reliable qubit. That’s because of another quantum mechanical property called “entanglement,” whereby the individual probabilities of each qubit can be affected by the other qubits in the system.

All of which means that the upper limit of a workable quantum computer’s power far exceeds what would be possible in classic computing.

So quantum computers could theoretically solve problems that a classic computer, no matter how powerful, never could. What kind of problems? How about the fundamental nature of material reality, which, after all, ultimately runs on quantum mechanics, not classical mechanics? (Sorry, Newton.) “Quantum computers simulate problems that we find in nature and in chemistry,” said Jay Gambetta, IBM’s vice president of quantum computing.

Quantum computers could simulate the properties of a theoretical battery to help design one that is far more efficient and powerful than today’s versions. They could untangle complex logistical problems, discover optimal delivery routes, or enhance forecasts for climate science.

On the security side, quantum computers could break cryptography methods, potentially rendering everything from emails to financial data to national secrets insecure — which is why the race for quantum supremacy is also an international competition, one that the Chinese government is pouring billions into. Those concerns helped prompt the White House earlier this month to release a new memorandum to architect national leadership in quantum computing and prepare the country for quantum-assisted cybersecurity threats.

Beyond the security issues, the potential financial upsides could be significant. Companies are already offering early quantum-computing services via the cloud for clients like Exxon Mobil and the Spanish bank BBVA. While the global quantum-computing market was worth less than $500 million in 2020, International Data Corporation projects that it will reach $8.6 billion in revenue by 2027, with more than $16 billion in investments.

But none of that will be possible unless researchers can do the hard engineering work of turning a quantum computer from what is still largely a scientific experiment into a reliable industry.

The cold room

Inside the Watson building, Jerry Chow — who directs IBM’s experimental quantum computer center — opened a 9-foot glass cube to show me something that looked like a chandelier made out of gold: IBM’s Quantum System One. Much of the chandelier is essentially a high-tech fridge, with coils that carry superfluids capable of cooling the hardware to 100th of a degree Celsius above absolute zero — colder, Chow told me, than outer space.

Refrigeration is key to making IBM’s quantum computers work, and it also demonstrates why doing so is such an engineering challenge. While quantum computers are potentially far more powerful than their classic counterparts, they’re also far, far more finicky.

Remember what I said about the quantum properties of superposition and entanglement? While qubits can do things a mere bit could never dream of, the slightest variation in temperature or noise or radiation can cause them to lose those properties through something called decoherence.

That fancy refrigeration is designed to keep the system’s qubits from decohering before the computer has completed its calculations. The very earliest superconducting qubits lost coherence in less than a nanosecond, while today IBM’s most advanced quantum computers can maintain coherence for as many as 400 microseconds. (Each second contains 1 million microseconds.)

The challenge IBM and other companies face is engineering quantum computers that are less error-prone while “scaling the systems beyond thousands or even tens of thousands of qubits to perhaps millions of them,” Chow said.

That could be years off. Last year, IBM introduced the Eagle, a 127-qubit processor, and in its new technical roadmap, it aims to unveil a 433-qubit processor called the Osprey later this year, and a 4,000-plus qubit computer by 2025. By that time, quantum computing could move beyond the experimentation phase, IBM CEO Arvind Krishna told reporters at a press event earlier this month.

Plenty of experts are skeptical that IBM or any of its competitors will ever get there, raising the possibility that the engineering problems presented by quantum computers are simply too hard for the systems to ever be truly reliable. “What’s happened over the last decade is that there have been a tremendous number of claims about the more immediate things you can do with a quantum computer, like solve all these machine learning problems,” Scott Aaronson, a quantum computing expert at the University of Texas, told me last year. “But these claims are about 90 percent bullshit.” To fulfill that promise, “you’re going to need some revolutionary development.”

In an increasingly digital world, further progress will depend on our ability to get ever more out of the computers we create. And that will depend on the work of researchers like Chow and his colleagues, toiling away in windowless labs to achieve a revolutionary new development around some of the hardest problems in computer engineering — and along the way, trying to build the future.

A version of this story was initially published in the Future Perfect newsletter. Sign up here to subscribe!

Update, October 4, 4 pm ET: This story was originally published on May 24 and has been updated to reflect that Clauser, Aspect, and Zeilinger were awarded the 2022 Nobel Prize in physics.

Tue, 04 Oct 2022 08:08:00 -0500 en text/html
Killexams : Artificial Intelligence In Marketing Global Market Report 2022: Featuring IBM, Salesforce, Amazon, Facebook & Oracle -

DUBLIN--(BUSINESS WIRE)--Oct 3, 2022--

The "Artificial Intelligence In Marketing Global Market Report 2022" report has been added to's offering.

The global artificial intelligence in marketing market is expected to grow from $13.51 billion in 2021 to $17.46 billion in 2022 at a compound annual growth rate (CAGR) of 29.25%. The artificial intelligence in marketing market is expected to grow to $48.91 billion in 2026 at a compound annual growth rate (CAGR) of 29.38%.

APAC was the largest region in the artificial intelligence in marketing market in 2021. The regions covered in the artificial intelligence in marketing market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The increasing adoption of virtual assistants is expected to drive the artificial intelligence in marketing market. Virtual assistants are services over the internet or dedicated network with delivery on demand. Due to the pandemic and lockdowns, small and medium-scale enterprises are increasingly focusing on streamlining their business models by adopting virtual assistants.

For instance, in April 2022, ThriveMyWay publisehd an article which states that chatbot ecommerce transactions is projected to hit $112 billion by 2023. Conversational technologies such as virtual agents and chatbots can help businesses save up to 30% on customer support costs. Hence, the increasing adoption of virtual assistants will increase the demand for artificial intelligence in the marketing market.

The advancement of technologies is seen as an emerging trend in artificial intelligence (AI) in marketing market. Software companies are bringing new advanced technology for automated and integrated business models. In October 2020, IBM planned to provide its IBM Watson, an AI for business toolset to industry leaders and make it available across the advertising ecosystem. Altering existing business practices can provide firms with improved AI capabilities in language, automation, and trust.

In March 2022, Zoomd Technologies Ltd., an Israel-based company marketing tech company announced the acquisition of Albert Technologies Ltd., for an undisclosed amount. Through this deal, Zoomd aims to expand its products onto a Self-Service and SaaS business model using Albert's expertise in artificial intelligence (AI) and add Fortune 500 customers that will now be able to use Zoomd products and services. Albert Technologies Ltd. is a US-based company offering artificial intelligence marketing solution.


Markets Covered:

1) By Technology: Machine Learning; Context-Aware Computing; Natural Language Processing; Computer Vision

2) By Offering: Hardware; Software; Services

3) By Deployment Type: Cloud; On Premises

4) By Application: Social Media Advertising; Search Advertising; Dynamic Pricing; Virtual Assistant; Content Curation; Sales And Marketing Automation; Analytics Platform; Others

Key syllabus Covered:

1. Executive Summary

2. Artificial Intelligence In Marketing Market Characteristics

3. Artificial Intelligence In Marketing Market Trends And Strategies

4. Impact Of COVID-19 On Artificial Intelligence In Marketing

5. Artificial Intelligence In Marketing Market Size And Growth

6. Artificial Intelligence In Marketing Market Segmentation

7. Artificial Intelligence In Marketing Market Regional And Country Analysis

8. Asia-Pacific Artificial Intelligence In Marketing Market

9. China Artificial Intelligence In Marketing Market

10. India Artificial Intelligence In Marketing Market

11. Japan Artificial Intelligence In Marketing Market

12. Australia Artificial Intelligence In Marketing Market

13. Indonesia Artificial Intelligence In Marketing Market

14. South Korea Artificial Intelligence In Marketing Market

15. Western Europe Artificial Intelligence In Marketing Market

16. UK Artificial Intelligence In Marketing Market

17. Germany Artificial Intelligence In Marketing Market

18. France Artificial Intelligence In Marketing Market

19. Eastern Europe Artificial Intelligence In Marketing Market

20. Russia Artificial Intelligence In Marketing Market

21. North America Artificial Intelligence In Marketing Market

22. USA Artificial Intelligence In Marketing Market

23. South America Artificial Intelligence In Marketing Market

24. Brazil Artificial Intelligence In Marketing Market

25. Middle East Artificial Intelligence In Marketing Market

26. Africa Artificial Intelligence In Marketing Market

27. Artificial Intelligence In Marketing Market Competitive Landscape And Company Profiles

28. Key Mergers And Acquisitions In The Artificial Intelligence In Marketing Market

29. Artificial Intelligence In Marketing Market Future Outlook and Potential Analysis

30. Appendix

Companies Mentioned

  • IBM
  • Salesforce
  • Amazon
  • Facebook
  • Oracle

For more information about this report visit

View source version on


Laura Wood, Senior Press Manager

For E.S.T Office Hours Call 1-917-300-0470

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SOURCE: Research and Markets

Copyright Business Wire 2022.

PUB: 10/03/2022 06:24 AM/DISC: 10/03/2022 06:24 AM

Mon, 03 Oct 2022 00:19:00 -0500 en text/html
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