Great Moments in Smart Software: IBM Watson Gets to Find Its Future Elsewhere Again

June 19, 2024

dinosaur30a_thumb_thumbThis essay is the work of a dinobaby. Unlike some folks, no smart software improved my native ineptness.

The smart software game is a tough one. Whip up some compute, download the models, and go go go. Unfortunately artificial intelligence is artificial and often not actually intelligent. I read an interesting article in Time Magazine (who knew it was still in business?). The story has a clickable title: “McDonald’s Ends Its Test Run of AI Drive-Throughs With IBM.” The juicy word IBM, the big brand McDonald’s, and the pickle on top: IBM.


A college student tells the smart software system at a local restaurant that his order was misinterpreted. Thanks, MSFT Copilot. How your “recall” today? What about system security? Oh, that’s too bad.

The write up reports with the glee of a kid getting a happy meal:

McDonald’s automated order taker with IBM received scores of complaints in recent years, for example — with many taking to social media to document the chatbot misunderstanding their orders.

Consequently, the IBM fast food service has been terminated.

Time’s write up included a statement from Big Blue too:

In an initial statement, IBM said that “this technology is proven to have some of the most comprehensive capabilities in the industry, fast and accurate in some of the most demanding conditions," but did not immediately respond to a request for further comment about specifics of potential challenges.

IBM suggested its technology could help fight cancer in Houston a few years ago. How did that work out? That smart software worker had an opportunity to find its future elsewhere. The career trajectory, at first glance, seems to be from medicine to grilling burgers. One might interpret this as an interesting employment trajectory. The path seems to be heading down to Sleepy Town.

What’s the future of the IBM smart software test? The write up points out:

Both IBM and McDonald’s maintained that, while their AI drive-throughs partnership was ending, the two would continue their relationship on other projects. McDonalds said that it still plans to use many of IBM’s products across its global system.

But Ronald McDonald has to be practical. The article adds:

In December, McDonald’s launched a multi-year partnership with Google Cloud. In addition to moving restaurant computations from servers into the cloud, the partnership is also set to apply generative AI “across a number of key business priorities” in restaurants around the world.

Google’s smart software has been snagged in some food controversies too. The firm’s smart system advised some Googlers to use glue to make the cheese topping stick better. Yum.

Several observations seem to be warranted:

  1. Practical and money-saving applications of IBM’s smart software do not have the snap, crackle, and pop of OpenAI’s PR coup with Microsoft in January 2023. Time is writing about IBM, but the case example is not one that makes me crave this particular application. Customers want a sandwich, not something they did not order.
  2. Examples of reliable smart software applications which require spontaneous reaction to people ordering food or asking basic questions are difficult to find. Very narrow applications of smart software do result in positive case examples; for example, in some law enforcement software (what I call policeware), the automatic processes of some vendors’ solutions work well; for example, automatic report generation in the Shadowdragon Horizon system.
  3. Big companies spend money, catch attention, and then have to spend more money to remediate and clean up the negative publicity.

Net net: More small-scale testing and less publicity chasing seem to be two items to add to the menu. And, Watson, keep on trying. Google is.

Stephen E Arnold, June 19, 2024


Taming AI Requires a Combo of AskJeeves and Watson Methods

April 15, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I spotted a short item called “A Faster, Better Way to Prevent an AI Chatbot from Giving Toxic Responses.” The operative words from my point of view are “faster” and “better.” The write up reports (with a serious tone, of course):

Teams of human testers write prompts aimed at triggering unsafe or toxic text from the model being tested. These prompts are used to teach the chatbot to avoid such responses.

Yep, AskJeeves created rules. As long as the users of the system asked a question for which there was a rule, the helpful servant worked; for example, What’s the weather in San Francisco? However, ask a question for which there was no rule, what happens? The search engine reality falls behind the marketing juice and gets shopped until a less magical version appears as And then there is IBM Watson. That system endeared itself to groups of physicians who were invited to answer IBM “experts’” questions about cancer treatments. I heard when Watson was in full medical-revolution mode that some docs in a certain Manhattan hospital used dirty words to express his view about the Watson method. Rumor or actual factual? I don’t know, but involving humans in making software smart can be fraught with challenges: Managerial and financial to name but two.


The write up says:

Researchers from Improbable AI Lab at MIT and the MIT-IBM Watson AI Lab used machine learning to improve red-teaming. They developed a technique to train a red-team large language model to automatically generate diverse prompts that trigger a wider range of undesirable responses from the chatbot being tested. They do this by teaching the red-team model to be curious when it writes prompts, and to focus on novel prompts that evoke toxic responses from the target model. The technique outperformed human testers and other machine-learning approaches by generating more distinct prompts that elicited increasingly toxic responses. Not only does their method significantly improve the coverage of inputs being tested compared to other automated methods, but it can also draw out toxic responses from a chatbot that had safeguards built into it by human experts.

How much improvement? Does the training stick or does it demonstrate that charming “Bayesian drift” which allows the probabilities to go walk-about, nibble some magic mushrooms, and generate fantastical answers? How long did the process take? Was it iterative? So many questions, and so few answers.

But for this group of AI wizards, the future is curiosity-driven red-teaming. Presumably the smart software will not get lost, suffer heat stroke, and hallucinate. No toxicity, please.

Stephen E Arnold, April 15, 2024

IBM and AI: A Spur to Other Ageing Companies?

March 27, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I love IBM. Well, I used to. Years ago I had three IBM PC 704 servers. Each was equipped with its expansion SCSI storage device. My love disappeared as we worked daily to keep the estimable ServeRAID softwware in tip top shape. For those unfamiliar with the thrill of ServeRAID, “tip top” means preventing the outstanding code from trashing data.


IBM is a winner. Thanks, MSFT Copilot. How are those server vulnerabilities today?

I was, therefore, not surprised to read “IBM Stock Nears an All-Time High—And It May Have Something to Do with its CEO Replacing As Many Workers with AI As Possible.” Instead of creating the first and best example of dinobaby substitution, Big Blue is now using smart software to reduce headcount. The write up says:

[IBM] used AI to reduce the number of employees working on relatively manual HR-related work to about 50 from 700 previously, which allowed them to focus on other things, he [Big Dog at IBM] wrote in an April commentary piece for Fortune. And in its January fourth quarter earnings, the company said it would cut costs in 2024 by $3 billion, up from $2 billion previously, in part by laying off thousands of workers—some of which it later chalked up to AI influence.

Is this development important? Yep. Here are the reasons:

  1. Despite its interesting track record in smart software, IBM has figured out it can add sizzle to the ageing giant by using smart software to reduce costs. Forget that cancer curing stuff. Go with straight humanoid replacement.
  2. The company has significant influence. Some Gen Y and Gen Z wizards don’t think about IBM. That’s fine, but banks, government agencies, Fortune 1000 firms, and family fund management firms do. What IBM does influences these bright entities’ thinking.
  3. The targeted workers are what one might call “expendable.” That’s a great way to motivate some of Big Blue’s war horses.

Net net: The future of AI is coming into focus for some outfits who may have a touch of arthritis.

Stephen E Arnold, March 27, 2024

IBM Charges Toward Consulting Services: Does Don Quixote Work at Big Blue?

January 23, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

It is official. IBM consultants will use smart software to provide answers to clients. Why not ask the smart software directly and skip the consultants? Why aren’t IBM consultants sufficiently informed and intelligent to answer a client’s questions directly? Is IBM admitting that its consultants lack the knowledge depth and insight necessary to solve a client’s problems? Hmmm.

IBM Introduces IBM Consulting Advantage, an AI Services Platform and Library of Assistants to Empower Consultants” asserts in corporate marketing lingo:

IBM Consulting Assistants are accessed through an intuitive conversational interface powered by IBM Watsonx, IBM’s AI and data platform. Consultants can toggle across multiple IBM and third-party generative AI models to compare outputs and select the right model for their task, and use the platform to rapidly build and share prompts and pre-trained assistants across teams or more widely across the consulting organization. The interface also enables easy uploading of project-specific documents for rapid insights that can then be shared into common business tools.

One of the key benefits of using smart software is to allow the IBM consultants to do more in the same billable hour. Thus, one can assume that billable hours will go up. “Efficiency” may not equate to revenue generation if the AI-assisted humanoids deliver incorrect, off-point, or unverifiable outputs.


A winner with a certain large company’s sure fire technology. Thanks, MSFT second string Copilot Bing thing. Good enough.

What can the AI-turbo charged system do? A lot. Here’s what IBM marketing asserts:

The IBM Consulting Advantage platform will be applied across the breadth of IBM Consulting’s services, spanning strategy, experience, technology and operations. It is designed to work in combination with IBM Garage, a proven, collaborative engagement model to help clients fast-track innovation, realize value three times faster than traditional approaches, and transparently track business outcomes. Today’s announcement builds on IBM Consulting’s concrete steps in 2023 to further expand its expertise, tools and methods to help accelerate clients’ business transformations with enterprise-grade AI…. IBM Consulting helps accelerate business transformation for our clients through hybrid cloud and AI technologies, leveraging our open ecosystem of partners. With deep industry expertise spanning strategy, experience design, technology, and operations, we have become the trusted partner to many of the world’s most innovative and valuable companies, helping modernize and secure their most complex systems. Our 160,000 consultants embrace an open way of working and apply our proven, collaborative engagement model, IBM Garage, to scale ideas into outcomes.

I have some questions; for example:

  1. Will IBM hire less qualified and less expensive humans, assuming that smart software lifts them up to super star status?
  2. Will the system be hallucination proof; that is, what procedure ensures that decisions based on smart software assisted outputs are based on factual, reliable information?
  3. When a consulting engagement goes off the rails, how will IBM allocate responsibility; for example, 100 percent to the human, 50 percent to the human and 50 percent to those who were involved in building the model, or 100 percent to the client since the client made a decision and consultants just provide options and recommendations?

I look forward to IBM Watsonx’s revolutionizing consulting related to migrating COBOL from a mainframe to a hybrid environment relying on a distributed network with diverse software. Will WatsonX participate in Jeopardy again?

Stephen E Arnold, January 23, 2024

IBM: AI Marketing Like It Was 2004

January 5, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required. Note: The word “dinobaby” is — I have heard — a coinage of IBM. The meaning is an old employee who is no longer wanted due to salary, health care costs, and grousing about how the “new” IBM is not the “old” IBM. I am a proud user of the term, and I want to switch my tail to the person who whipped up the word.

What’s the future of AI? The answer depends on whom one asks. IBM, however, wants to give it the old college try and answer the question so people forget about the Era of Watson. There’s a new Watson in town, or at least, there is a new Watson at the old IBM url. IBM has an interesting cluster of information on its Web site. The heading is “Forward Thinking: Experts Reveal What’s Next for AI.”

IBM crows that it “spoke with 30 artificial intelligence visionaries to learn what it will take to push the technology to the next level.” Five of these interviews are now available on the IBM Web site. My hunch is that IBM will post new interviews, hit the new release button, post some links on social media, and then hit the “Reply” button.


Can IBM ignite excitement and capture the revenues it wants from artificial intelligence? That’s a good question, and I want to ask the expert in the cartoon for an answer. Unfortunately only customers and their decisions matter for AI thought leaders unless the intended audience is start ups, professors, and employees. Thanks, MSFT Copilot Bing thing. Good enough.

As I read the interviews, I thought about the challenge of predicting where smart software would go as it moved toward its “what’s next.” Here’s a mini-glimpse of what the IBM visionaries have to offer. Note that I asked Microsoft’s smart software to create an image capturing the expert sitting in an office surrounded by memorabilia.

Kevin Kelly (the author of What Technology Wants) says: “Throughout the business world, every company these days is basically in the data business and they’re going to need AI to civilize and digest big data and make sense out of it—big data without AI is a big headache.” My thought is that IBM is going to make clear that it can help companies with deep pockets tackle these big data and AI them. Does AI want something, or do those trying to generate revenue want something?

Mark Sagar (creator of BabyX) says: “We have had an exponential rise in the amount of video posted online through social media, etc. The increased use of video analysis in conjunction with contextual analysis will end up being an extremely important learning resource for recognizing all kinds of aspects of behavior and situations. This will have wide ranging social impact from security to training to more general knowledge for machines.” Maybe IBM will TikTok itself?

Chieko Asakawa (an unsighted IBM professional) says: “We use machine learning to teach the system to leverage sensors in smartphones as well as Bluetooth radio waves from beacons to determine your location. To provide detailed information that the visually impaired need to explore the real world, beacons have to be placed between every 5 to 10 meters. These can be built into building structures pretty easily today.” I wonder if the technology has surveillance utility?

Yoshua Bengio (seller of an AI company to ServiceNow) says: “AI will allow for much more personalized medicine and bring a revolution in the use of large medical datasets.” IBM appears to have forgotten about its Houston medical adventure and Mr. Bengio found it not worth mentioning I assume.

Margaret Boden (a former Harvard professor without much of a connection to Harvard’s made up data and administrative turmoil) says: “Right now, many of us come at AI from within our own silos and that’s holding us back.” Aren’t silos necessary for security, protecting intellectual property, and getting tenure? Probably the “silobreaking” will become a reality.

Several observations:

  1. IBM is clearly trying hard to market itself as a thought leader in artificial intelligence. The Jeopardy play did not warrant a replay.
  2. IBM is spending money to position itself as a Big Dog pulling the AI sleigh. The MIT tie up and this AI Web extravaganza are evidence that IBM is [a] afraid of flubbing again, [b] going to market its way to importance, [c] trying to get traction as outfits like OpenAI, Mistral, and others capture attention in the US and Europe.
  3. IBM’s ability to generate awareness of its thought leadership in AI underscores one of the challenges the firm faces in 2024.

Net net: The company that coined the term “dinobaby” has its work cut out for itself in my opinion. Is Jeopardy looking like a channel again?

Stephen E Arnold, January 5, 2024

Profits Over Promises: IBM Sells Facial Recognition Tech to British Government

September 18, 2023

Just three years after it swore off any involvement in facial recognition software, IBM has made an about-face. The Verge reports, “IBM Promised to Back Off Facial Recognition—Then it Signed a $69.8 Million Contract to Provide It.” Amid the momentous Black Lives Matter protests of 2020, IBM’s Arvind Krishna wrote a letter to Congress vowing to no longer supply “general purpose” facial recognition tech. However, it appears that is exactly what the company includes within the biometrics platform it just sold to the British government. Reporter Mark Wilding writes:

“The platform will allow photos of individuals to be matched against images stored on a database — what is sometimes known as a ‘one-to-many’ matching system. In September 2020, IBM described such ‘one-to-many’ matching systems as ‘the type of facial recognition technology most likely to be used for mass surveillance, racial profiling, or other violations of human rights.'”

In the face of this lucrative contract IBM has changed its tune. It now insists one-to-many matching tech does not count as “general purpose” since the intention here is to use it within a narrow scope. But scopes have a nasty habit of widening to fit the available tech. The write-up continues:

“Matt Mahmoudi, PhD, tech researcher at Amnesty International, said: ‘The research across the globe is clear; there is no application of one-to-many facial recognition that is compatible with human rights law, and companies — including IBM — must therefore cease its sale, and honor their earlier statements to sunset these tools, even and especially in the context of law and immigration enforcement where the rights implications are compounding.’ Police use of facial recognition has been linked to wrongful arrests in the US and has been challenged in the UK courts. In 2019, an independent report on the London Metropolitan Police Service’s use of live facial recognition found there was no ‘explicit legal basis’ for the force’s use of the technology and raised concerns that it may have breached human rights law. In August of the following year, the UK’s Court of Appeal ruled that South Wales Police’s use of facial recognition technology breached privacy rights and broke equality laws.”

Wilding notes other companies similarly promised to renounce facial recognition technology in 2020, including Amazon and Microsoft. Will governments also be able to entice them into breaking their vows with tantalizing offers?

Cynthia Murrell, September 18, 2023

A Perfect Plan: Mainframes Will Live Forever

September 7, 2023

Vea4_thumb_thumb_thumb_thumb_thumb_tNote: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

Experienced COBOL programmers are in high demand and short supply, but IBM is about to release an AI tool that might render that lucrative position obsolete. The Register reports: “IBM Says GenAI Can Convert that Old COBOL Code to Java for You.” Dubbed the watsonx Code Assistant for Z, the tool should be available near the end of this year. Reporter Dan Robinson gives us a little background:

“COBOL supports many vital processes within organizations globally – some that would surprise newbie devs. The language was designed specifically to be portable and easier for coding business applications. The good news is that it works. The bad news is it’s been working for a little long. COBOL has been around for over 60 years, and many of the developers who wrote those applications have since retired or are no longer with us. ‘If you can find a COBOL programmer, they are expensive. I have seen figures showing they can command some of the highest salaries because so many mission critical apps are written in COBOL and they need maintenance,’ Omdia Chief Analyst Roy Illsley told us.

Migrating the code to Java means there are many more programmers around, he added, and if the apps run on Linux on Z then they can potentially be moved off the mainframe more easily in future.”

Perhaps. There are an estimated 775 to 850 billion lines of COBOL code at work in the business world, and IBM is positioning Code Assistant to help prioritize, refactor, and convert them all into Java. There is just one pesky problem:

“IBM is not the only IT outfit turning to AI tools to help developers code or maintain applications, however, the quality of AI-assisted output has been questioned. A Stanford University study found that programmers who accepted help from AI tools like Github Copilot produce less secure code than those who did not.”

So maybe firms should hold on to those COBOL programmers’ contact info, just in case.

Cynthia Murrell, September 7, 2023

IBM and Smart Software: Try and Try Again, Dear Watson with an X

August 7, 2023

Vea4_thumb_thumb_thumb_thumb_thumb_tNote: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

With high hopes, IBM is acquiring FinOps firm Apptio for $4.6 billion. As Horses for Sources puts it, “IBM’s Acquisition of Apptio Can Shine if IBM Software and IBM Consulting Work Together to Deliver Cost-Managed Innovation at Speed.” But that is a big “if”. The odds seem long from the standpoint of RedHat users unimpressed with both IBM’s approach and internal cooperation at the company.

8 6 kid stacking blocks

The young, sincere child presages her future in a giant technology company, “Yes, I will try to stack blocks to make the big building you told me to create with the blocks I got from my friend, Apt Ti Oh.” MidJourney, you did let me down with your previous “frustrated kid” images. Sultry teens were not what I was after.

IBM intends to mix Apptio with several other acquisitions that have gone into the new Watsonx platform, like Turbonomic, Instana, and MyInvenio, to create a cohesive IT-management platform. Linking spending data with operational data should boost efficiency, save money, and facilitate effective planning. This vision, however, is met with some skepticism. Writers Tom Reuner and Phil Fersht tell us:

“Apptio never progressed beyond providing insights, while IBM needs to demonstrate the proof points for integrating its disparate capabilities as well as progress from insight to action and, ultimately, automation. IBM Software must work with IBM Consulting transformation more effectively. … In essence, if successful, the ability to act on – and ultimately automate – all those insights is pretty much the operational Holy Grail. Just for transparency, getting expansive spend management and FinOps capabilities in itself will be a solid asset for IBM. However, any new and bolder proposition aiming at the bigger transformation price must move beyond technology and include stakeholders and change management. The ambition could be a broader business assurance where spend data, operational insights, and governance get tied to business objectives.  In our view, this provides a significant alignment opportunity with IBM Consulting as it seeks to differentiate itself from the likes of Accenture Operations and Genpact.  Having a deep services alignment with Watsonx and Apptio will bridge together the ability to manage the cost and value of both cloud transformation and AI investments – provided it gets it right with its global talent base of technical and process domain specialists.”

So the objective is a platform that brings companies’ disparate parts together into a cohesive and efficient whole. But this process must involve humans as well as data. If IBM can figure out how to do so within its own company, perhaps it stands a chance of reaching the goal.

Cynthia Murrell, August 6, 2023

Quantum Seeks Succor Amidst the AI Tsunami

July 5, 2023

Vea4_thumb_thumb_thumb_thumb_thumb_t[1]Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

Imagine the heartbreak of a quantum wizard in the midst of the artificial intelligence tsunami. What can a “just around the corner” technology do to avoid being washed down the drain? The answer is public relations, media coverage, fascinating announcements. And what companies are practicing this dark art of outputting words instead of fully functional, ready-to-use solutions?

Give up?

I suggest that Google and IBM are the dominant players. Imagine an online ad outfit and a consulting firm with mainframes working overtime to make quantum computing exciting again. Frankly I am surprised that Intel has not climbed on its technology stallion and ridden Horse Ridge or Horse whatever into PR Land. But, hey, one has to take what one’s newsfeed delivers. The first 48 hours of July 2023 produced two interesting items.

The first is “Supercomputer Makes Calculations in Blink of an Eye That Take Rivals 47 Years.” The write up is about the Alphabet Google YouTube construct and asserts:

While the 2019 machine had 53 qubits, the building blocks of quantum computers, the next generation device has 70. Adding more qubits improves a quantum computer’s power exponentially, meaning the new machine is 241 million times more powerful than the 2019 machine. The researchers said it would take Frontier, the world’s leading supercomputer, 6.18 seconds to match a calculation from Google’s 53-qubit computer from 2019. In comparison, it would take 47.2 years to match its latest one. The researchers also claim that their latest quantum computer is more powerful than demonstrations from a Chinese lab which is seen as a leader in the field.

Can one see this fantastic machine which is 241 million times more powerful than the 2019 machine? Well, one can see a paper which talks about the machine. That is good enough for the Yahoo real news report. What do the Chinese, who have been kicked to the side of the Information Superhighway, say? Are you joking? That would be work. Writing about a Google paper and calling around is sufficient.

If you want to explore the source of this revelation, navigate to “Phase Transition in Random Circuit Sampling.” Note that the author has more than 175 authors is available from at The list of authors does not appear in the PDF until page 37 (see below) and only about 80 appear on the abstract page on the ArXiv splash page. I scanned the list of authors and I did not see Jeff Dean’s name. Dr. Dean is/was a Big Dog at the Google but …


Just to make darned sure that Google’s Quantum Supremacy is recognized, the organizations paddling the AGY marketing stream include NASA, NIST, Harvard, and more than a dozen computing Merlins. So there! (Does AGY have an inferiority complex?)

The second quantum goody is the write up “IBM Unlocks Quantum Utility With its 127-Qubit “Eagle” Quantum Processing Unit.” The write up reports as actual factual IBM’s superior leap frogging quantum innovation; to wit, coping with noise and knowing if the results are accurate. The article says via a quote from an expert:

The crux of the work is that we can now use all 127 of Eagle’s qubits to run a pretty sizable and deep circuit — and the numbers come out correct

The write up explains:

The work done by IBM here has already had impact on the company’s [IBM’s] roadmap – ZNE has that appealing quality of making better qubits out of those we already can control within a Quantum Processing Unit (QPU). It’s almost as if we had a megahertz increase – more performance (less noise) without any additional logic. We can be sure these lessons are being considered and implemented wherever possible on the road to a “million + qubits”.

Can one access this new IBM approach? Well, there is this article and a chart.

Which quantum innovation is the more significant? In terms of putting the technology in one laptop, not much. Perhaps one can use the system via the cloud? Some may be able to get outputs… with permission of course.

But which is the PR winner? In my opinion, the Google wins because it presents a description of a concept with more authors. IBM, get your marketing in gear. By the way, what’s going on with the RedHat dust up? Quantum news releases won’t make that open source hassle go away. And, Google, the quantum stuff and the legion of authors is unlikely to impress European regulators.

And why make quantum noises before a US national holiday? My hunch is that quantum is perfect holiday fodder. My question, “When will the burgers be done?”

Stephen E Arnold, July 5, 2023

The Return: IBM Watsonx!

May 26, 2023

Vea4_thumb_thumb_thumb_thumb_thumb_t[1]Note: This essay is the work of a real and still-alive dinobaby. No smart software involved, just a dumb humanoid.

It is no surprise IBM’s entry into the recent generative AI hubbub is a version of Watson, the company’s longtime algorithmic representative. Techspot reports, “IBM Unleashes New AI Strategy with ‘watsonx’.” The new suite of tools was announced at the company’s recent Think conference. Note “watsonx” is not interchangeable with “Watson.” The older name with the capital letter and no trendy “x” is to be used for tools individuals rather than company-wide software. That won’t be confusing at all. Writer Bob O’Donnell describes the three components of watsonx:

“ is the core AI toolset through which companies can build, train, validate and deploy foundation models. Notably, companies can use it to create original models or customize existing foundation models., is a datastore optimized for AI workloads that’s used to gather, organize, clean and feed data sources that go into those models. Finally, watsonx.governance is a tool for tracking the process of the model’s creation, providing an auditable record of all the data going into the model, how it’s created and more.Another part of IBM’s announcement was the debut of several of its own foundation models that can be used with the watsonx toolset or on their own. Not unlike others, IBM is initially unveiling a LLM-based offering for text-based applications, as well as a code generating and reviewing tool. In addition, the company previewed that it intends to create some additional industry and application-specific models, including ones for geospatial, chemistry, and IT operations applications among others. Critically, IBM said that companies can run these models in the cloud as a service, in a customer’s own data center, or in a hybrid model that leverages both. This is an interesting differentiation because, at the moment, most model providers are not yet letting organizations run their models on premises.”

Just to make things confusing, er, offer more options, each of these three applications will have three different model architectures. On top of that, each of these models will be available with varying numbers of parameters. The idea is not, as it might seem, to give companies decision paralysis but to provide flexibility in cost-performance tradeoffs and computing requirements. O’Donnell notes watsonx can also be used with open-source models, which is helpful since many organizations currently lack staff able build their own models.

The article notes that, despite the announcement’s strategic timing, it is clear watsonx marks a change in IBM’s approach to software that has been in the works for years: generative AI will be front and center for the foreseeable future. Kinda like society as a whole, apparently.

Cynthia Murrell, May 26, 2023

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