Serendipity35

It is difficult to keep up with AI advances and new tools. Recently, I have seen the term "superintelligence" being used and I had to look for a definition.

In AI terms, there are three kinds of intelligence. "Artificial Narrow Intelligence" is what we have now. It is "superhuman" at specific tasks like playing Go or translating languages. ChatGPT, Gemini, CoPilot and Meta AI, et al fit in there at the moment.

"Artificial General Intelligence (AGI)" is human-level across the board and can learn anything a person can learn. We’re not quite there yet as of May 2026.

"Artificial Superintelligence (ASI)" is far beyond human level. Philosopher Nick Bostrom popularized the term: and defined it as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest.”

ASI is what people worry about — or get excited about — when talking about advanced AI. But AGI isn't quite the same as superintelligence. With AGI, you clone the best human brain in software, but with superintelligence that clone keeps upgrading itself until it’s as far beyond us. 

Two new tools are moving closer to the next level.

Google has released TurboQuant, a new compression method that makes AI models cheaper to run and faster to respond. In Google’s reported tests, it reduced the key-value cache, the model’s short-term working memory while it responds, by at least 6x and improved performance by up to 8x on H100 chips, Nvidia’s high-end AI processors used in data centres, while keeping benchmark performance, or standard test performance, close to the original model. That is a serious technical result with a clear business consequence: one of the biggest cost pressures in modern AI may begin to ease. For the past two years, the default logic has been simple. The best AI stayed in the cloud because that is where companies could absorb the cost of running it. TurboQuant starts to weaken that logic.

Meta TRIBE v2 is a foundation AI model that acts like a “digital twin” of the human brain. In plain terms, it’s an AI trained on real brain scan data so it can predict how a person’s brain will respond to things they see, hear, or read. It takes in video, audio, and text, then maps that to about 70,000 areas of the brain to simulate neural activity.  Meta itself says that you can think of it as Meta teaching an AI to “think” more as humans do, by learning directly from brain responses instead of just internet text.

Where did I get information anout Meta's products and path? From their own Muse Spark. That is Meta’s latest (well, as of today) AI assistant model.

This AI Hub from Microsoft & The OU is a collection allowing you to explore free, accessible courses designed to build your confidence and skills in artificial intelligence. Whether you’re just starting out or looking to deepen your knowledge, the AI Hub will support your learning journey with expert-led, trusted, easy-to-use resources created by The OU and Microsoft.

Not labeled as a MOOC (a term that seems to have fallen away in the past decade) it is a similar kind of open course, not for credit but for learning.

AI Fluency is a beginner-friendly learning path designed to build confidence and understanding in artificial intelligence. Through a series of practical sessions, learners explore AI fundamentals, generative AI, responsible AI principles, and the real-world impact of AI across work, accessibility, and society. The course also introduces Microsoft Copilot, showing how AI tools can support creativity, productivity, and everyday problem solving. 
Suitable for students, professionals, and leaders alike, AI fluency helps demystify AI and equips learners with the knowledge to engage with AI technologies thoughtfully, responsibly, and effectively.

Work Smarter with AI is a 65 minute, one module, learning path to help you work better and unleash your creativity with Microsoft Copilot. In this learning path, you'll explore how to use Microsoft Copilot to help you research, find information, and generate effective content. 
Prerequisites: Familiarity with Microsoft productivity applications, like Word, Excel, Outlook, and PowerPoint.

If you’ve found yourself both fascinated and/or unsettled by the accelerating pace of artificial intelligence, THE AI DOC; OR HOW I BECAME AN APOCALOPTIMIST offers one way to lean into that tension rather than avoid it.

This week it was my film for the Film Matinee Club with Montclair Film. Our discussion after viewing the film was "spirited." Artificial intelligence certainly pushes people's intellectual and emotional buttons.

Directed by Daniel Roher and Charlie Tyrell and hosted by Roher. It is about making a documentary, and it is about AI, and it is also a personal narrative centered on Roher’s own fears about the future, especially as he and his wife contemplate having their first child in an AI-driven world.

Across all sources, the documentary’s expert roster includes top AI CEOs, pioneering researchers, alignment and ethics leaders, and public intellectuals. The film intentionally spans “doomers,” “optimists,” and “apocaloptimists,” giving a wide-angle view of the AI debate.

Roher becomes an Apocal (as in apocalypse) optimist because (spoiler alert) as he learns more and understands AI's capabilities, he begins to see more positive possibilities. And yet the answer to whether AI will cause the end of us or make our lives very much improved is still an open question. Even the experts don't know no matter what side they take on the AI debate.

The film very deliberately does not settle on a single answer about the future of AI. The film’s whole structure is built around the tension between optimism and existential risk, and it ends by embracing that unresolved state rather than resolving it./p>

The phrase that if an app is free, you are the product means that when an app doesn’t charge you money, it usually makes money from you instead. They do that mainly by collecting your data or selling your attention to advertisers.

If that is true, then how is AI changing what that means? It is a question that deserves several posts here to really answer.

Your behavior, preferences, and time become what is being monetized. Your data becomes the product. Free apps often gather your demographics, browsing or in-app behavior, location, interests, and habits. This information is then used to target ads or sold to third parties.

The addictive nature of app design keeps you scrolling, tapping, or watching so they can show you ads. You pay with time, not dollars. “Free” is a business model, not a gift.

I will give these companies a nod that running an app costs money (servers, engineers, storage). If you are not paying, the company must earn revenue another way. Ad-free options are becoming more common as a premium. You have probably noticed that on apps and also on video streaming services. You thought that paying for Amazon Prime meant no ads on the videos. Wrong. Free is often an illusion.

In the world of AI, the difference between free and paid tiers is more than a matter of convenience. It is also about identity and privacy.

Privacy becomes the hidden cost. Data is currency. Companies track you across apps and devices, build detailed behavioral profiles, and use algorithms to influence what you see. This raises concerns about autonomy and consent.

Is there no stopping them? As long as you agree to their terms, they have a lot of power. BUT you can read those terms and privacy settings more carefully. (They rely on the fact that many users don't read the terms or adjust their settings at all.) Educate yourself and understand how digital ecosystems make money. You can choose paid or privacy-focused alternatives. And you can remove the app entirely from your life.

I see comparisons of using AI to using social media platforms. I don't think AI data is the same as social media data. Social media platforms monetize your attention. The longer you scroll, the more ads they can show. AI chatbots operate on a different axis. Your prompts aren’t just content; they’re training signals. They reveal how people think, what they struggle with, what they’re curious about, and how they phrase questions. Maybe it is anonymized (a good thing) but it is still valuable and often sensitive data.

Alarmist articles will remind you that many free AI chatbots use your prompts, your corrections, and your uploaded files. They have that photo of your family that you let them enhance. What will they do with what you give them? I can't answer that as of now, and certainly not for the future. I know that your conversation history is used to train or fine-tune future versions of the model. Hey, you are part of the product pipeline - but don't expect to be paid for your contributions.

I also concede that the business model matters and that different AI companies monetize differently. For example, Microsoft provides its own privacy commitments and policies, and those govern how your data is handled. For details, they always direct users to their Privacy Statement.

Here are 4 business models currently out there:
Ad-supported = Your attention is monetized.
Freemium = Free tier gathers usage; paid tier subsidizes development.
Enterprise licensing = Your data may be isolated; the company earns from businesses.
Open source =  The model is free; the company may sell hosting or support.

So "if an app is free, you are the product" still applies, but not always in the same way. When an AI tool is free, you’re not just the product — you’re also the collaborator. You’re an unpaid teacher, tester, and a source of fuel for improvement.