AI Top-of-Mind for Jan 30
As a follow-up to my earlier posting by Nir Zicherman, he now looks at the opposite question — how AI doesn’t work. From his writing:
· Two weeks ago, I published an article entitled How AI Works, in which I explained the fundamentals of today’s large language models (LLMs) without any complicated technical or mathematical language (opting instead to use analogies to food and meal planning).
· Since, I’ve been thinking about the many implications of those fundamentals. Namely, the inverse question: now that we know what AI can do, what can it not do?
Following down the ‘doesn’t work’ path, more on the true cost of AI and how it is in cases unsustainable. Will Lockett in ‘Predicts’ writes:
Not only does this research vindicate my opinion that Tesla’s claims that, shortly, all their cars will be driverless are effectively shilling snake oil, but it also indicates that the AI revolution is still far, far in the future. What’s more, it’s not like the costs associated with AI will drop any time soon, as the researchers theorised might happen. In fact, considering geopolitics, the crucial silicone chips that are needed to power AI could skyrocket in price soon! In short, you can sleep soundly knowing that robots aren’t going to render your job obsolete for a good while.
On the continuing battles between Microsoft, Google, and AWS for AI corporate dominance. Includes some good analysis of GitHub and GitLab code repositories. From ‘The Information’ for those with access:
It’s no secret that developers have flocked to GitHub Copilot, an AI-powered coding assistant Microsoft developed with OpenAI. But Microsoft is making strides toward its bigger goal: convincing those customers to also rent its Azure cloud servers — a higher-margin business than the AI.
Turning to marketing, another survey on changes to marketing spend mix on the back of AI. One term the ‘MediaPost’ article defines is ‘commerce marketing,’ a combination of performance marketing, commerce content, and affiliate marketing.
And from education, a recent symposium at MIT where a number of novel AI use cases were demonstrated. The ‘MIT Open Learning’ article looks at:
· Valfee: Helping students with public speaking
· MIT Personal Robots group: Helping students learn and flourish
· MIT App Inventor: Harnessing the power of generative AI
· Aptly: Turning ideas into working apps
Two items related to our past. The first looks at how AI finally mastered the game of ‘Go,’ a task much more difficult than chess. As Erik Brown at ‘Teatime History’ quotes Google:
Demis Hassabis Co-Founder & CEO of Google’s DeepMind says in Chess the number of possible moves per position is twenty, but in Go it’s two hundred. Plus, the number of possible “configurations on the board is more than the number of atoms in the universe.”
And the second published at ‘Open Culture’ looks back at ‘Eliza,’ the original chatbot and how it is still relevant today. The online version is here.
Finally, if you didn’t get enough embedded AI at CES, here is taking it to the extreme!
