The Increasingly Anti-Competitive World of AI

Cognilytica Insights

?? What can possibly go wrong when you embed someone else’s AI models in your systems?

Quite a lot. Especially when you have little control or visibility into those models.

Yet, despite the increasingly walled garden that is becoming the Large Language Models (LLMs) such as OpenAI’s ChatGPT, organizations are creating and embedding AI solutions powered by third-party models they have little visibility and control into.

Furthermore, the incumbent platform vendors such as Microsoft, Amazon, Google, and others have been making large investments and establishing control positions in some of the most critical AI systems being embedded in the vast majority of solutions being implemented.?

We already saw what that sort of “strategic investor” driven control means during the drama that was the short-term firing and re-hiring of OpenAI CEO Sam Altman a few months ago. Microsoft pulled their investor strings to ensure not only the continued value of their investment, but also that the solutions increasingly dependent on those OpenAI models continue to develop the way that Microsoft and others want them to develop.

?? What’s Going on with these AI “Partnerships”?

In recent years megatech companies established venture arms to invest in the latest new startups. These megatech companies have even dwarfed the funding rounds of the major venture capital firms. Some have reported that the tech companies are starting to push out VC as the most strategic investors in the space.?

With the recent surge of interest in generative AI, mega tech companies are in the race for AI dominance. There are only two ways to dominate with new technology: build or buy. The industry is moving way too fast to build your way to dominance.?

However, a straight-out acquisition of rapidly growing, emerging tech companies might scare away companies who are still early in their AI adoption. So, rather than just acquire companies like OpenAI, Anthropic, and others, companies like Microsoft, Alphabet (Google), Meta, and AWS are simply investing heavily in them as “partners”.

??? The FTC has recently launched an inquiry into Generative AI Investments and Partnerships. The FTC has launched a major inquiry into generative AI, focusing on investments and partnerships among key tech players like Alphabet, Amazon, and Microsoft.? The FTC’s move aims to scrutinize the competitive dynamics within the AI sector, ensuring innovation and fairness.? They are conducting? studies that allow enforcers to gain a deeper understanding of market trends and business practices, and dive deeper into what might be anti-competitive behavior in the AI industry.

Whoever shapes the vendor landscape for today’s AI solutions will absolutely dominate the space as organizations embed increasingly greater amounts of AI solutions in their applications, and both the incumbent megatech companies as well as the FTC realize that.

?? Real, Actual Open Source as an Antidote

Just a few years ago, there were very few models in the market that you could use off-the-shelf and embed in your solutions with a high degree of relevancy and performance.?

“Back in the day” if you wanted to build any NLP application such as a chatbot or sentiment analysis solution, or a computer vision application such as image or object recognition, or predictive analytics applications, or really any of the Seven Patterns of AI, you had to start from scratch. You started with the business understanding, then developed and prepared your data, built and evaluated the models, and operationalized them in the cloud or in your local environment: the six phases of CPMAI.

Now broad Foundation Models including generative AI solutions and LLMs have shortcut many of those steps. While you still need to implement the six phases of CPMAI to deliver a successful AI solution, you don’t have to build the models from scratch. You don’t have to develop and prepare large training data sets or spend the time and effort of GPU-based training. You don’t have to spend the effort optimizing hyperparameters and building ensemble models. The models are there for you, right now, off the shelf for you to just make an API call or execute with a single line or two of Python code. So why bother with the “old school” approach?

The broad applicability of the Foundation Models is very appealing. But the dangers of a new form of vendor lock-in are growing. The more we depend on these Foundation Models, the more bad things can happen, from changes to the behavior and performance of the solutions, to capabilities being removed from “free” offerings to more expensive paid ones, to platform moderation and regulatory responses causing the systems to respond increasingly poorly to your needs.

?? What Does This mean for you?

Organizations looking to implement AI in their applications have a variety of choices they can make:

• Build your own models from scratch (“the old way”)
• Use a single-vendor Foundation Model (“the fast way”)
• Combine multiple vendor Foundation Models (“the unsure if this actually works way”)
• Use open source Foundation models (“the safe way”)

It’s this last choice that’s the most compelling currently. There are a number of models in which not only the model is available for download, use, and embedding today, for free, but also you can peer into the model’s code, the details, and weights of the final trained model so you can make changes yourself, and all aspects of the training data and configuration.?

And, many of those models are performing just as well as the not-so-open alternatives on the market today, even the ones that use “Open” in their company name. Stay tuned as we dig more into the details of Open Source AI models in an upcoming AI Today podcast episode!

AI Best Practices: Latest Insights

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?? Events and Opportunities to Hear from Cognilytica

• THIS WEEK Feb. 7, 2024: PMI Silicon Valley Chapter - “How to Run Successful AI Projects and Avoid Failure” - PM Insight-Fremont Virtual Meeting, Virtual / Online session - 6:00PM to 8:00PM Pacific Time (PT). Earn 2 PDUs! [Register here]
• THIS WEEK Feb. 7, 2024: Tech Duels: Augmented vs Artificial Intelligence Debate: 5:30-8:30pm Eastern Time (ET) at George Mason University, Arlington, VA. Use code “TDPARTNER” for 50% discount on tickets. [Register here]
• March 7, 2024: PMI Houston, TX Chapter: “Running AI Projects Successfully” Virtual / Online session, 5:30 to 6:30pm Central Time ?- ?[Registration opening soon]
• March 20, 2024: PMI Metropolitan St. Louis Chapter: “Running Successful AI Projects and Avoiding Failure”: Virtual/Online session, 6:30pm-7:30pm CT. Participants will receive 1 PDU for this session. - ?[Registration opening soon]
• March 21, 2024: PMI Pikes Peak, CO Chapter: “ Winning Tactics for AI Implementation Success” Virtual / Online session - 12pm-1pm MT [Registration opening soon]
• March 26, 2024: PMI (North) Carolina Chapter: “What you need to know, today, to successfully run and manage AI projects” Virtual / Online session -? 6-7pm Eastern Time, [Registration opening soon]
• April 8, 2024: PMI Southern New England: “How to Run Successful AI Projects and Avoid Failure” - Session during SNEC-PMI's 16th Annual Conference in person in Hartford, CT. [Register here]
• April 29, 2024: PMI Saudi Arabia Chapter: “How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session -? 6PM-7PM Saudi Time (10AM-11AM Eastern Time) [Registration opening soon]
• May 7, 2024: PMI Delaware Valley Chapter - ‘How to Run Successful AI Projects and Avoid Failure”, Virtual / Online session -? 6:30PM-8PM Eastern Time [Registration opening soon]
• July 10, 2024: PMI Madrid, Spain Chapter: “Best Practice Methods for Successful AI Projects”, Virtual / Online session - 7:00 - 8:00 PM Spanish time? [Registration opening soon]
• July 10th, 2024: PMI San Francisco Chapter - “Successful approaches to running AI Projects - Avoiding the Top Reasons why AI Projects Fail”, Virtual / Online session -? 6-7:30 pm PST [Registration opening soon]

?? Move Forward with AI Best Practices - Training amp; Certification

Cognilytica’s AI best practices & Trustworthy training and certification continues to be in high demand. Haven’t yet enrolled in a certification or training? What’s holding you back?

• ?? CPMAI v7 - Get Certified with comprehensive AI & ML Project Management Training. Includes: AI Fundamentals, AI Applications, Managing Data for AI, Data Preparation for AI, ML Algorithms, Generative AI, CPMAI Methodology, and Trustworthy AI. - [Enroll now]
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Trustworthy AI: Latest Insights

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• ?? {Government} - FCC moves to outlaw AI-generated robocalls - In the wake of the upcoming US political election season, the FCC is proposing to make the? use of voice cloning tech in robocalls be ruled fundamentally illegal. This would make it easier to charge the operators of these frauds. Will this stop the criminals?[Read More]
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• ??♀ {Responsible AI} - Parcel delivery firm faces PR nightmare after AI-powered chatbot cusses and mocks the company. Are people really putting Gen AI solutions in place with no humans in the loop? [Read More]

??? What our Community is Saying

“Cognilytica’s CPMAI project management training and certification is a very effective program for executives and managers. Having taken this training early on in our AI journey, it provided me with a solid framework needed to successfully guide and provide meaningful oversight to our AI and ML projects. The CPMAI certification provides the needed? fundamentals to understand AI & machine learning with a big emphasis on how to do AI projects right. CPMAI training and certification is a must for anyone looking to run and manage AI projects of any size.” - Mahesh?Vinayagam, qBotica?

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