Check out my latest article: Decision Support to Organizational Semantics. summarizes a journal paper on research issues for AI-assisted decision support in organizations. via @LinkedIn.

If the O-S community can not establish a standard quickly, then it is 'each to his/her own' legal wishes. Meanwhile, AI innovator (and consumer) beware! 😮.

I recommend study of excellent in-depth paper by Sarah West of AI Now Institute. .The article confirms the chaos reigning within the entire industry and concludes with slim hopes placed on OSI, RAIL, ImpACT Licenses, and Tidelift.

MIT Technology Review just posted insightful article on "Tech Industry Can't Agree on What Open-Source AI Means". This has been bugging me for months: What does it mean? Does it matter? What are implications for “ethical, trustworthy, or responsible” AI?.

How do we prepare managers to properly use these AI capabilities? What will be the evolving role of the biz analyst? Will corporate IT become dependent on some proprietary LxM?.

BUT. Can we apply AI tech reliably and safely to managing our complex organizations of today? What will be the infrastructure required? Same as current, or a total rewrite?.

Listening to analyst briefing soon on Tableau Pulse. My question is how how will this new AI tech impact evolution of Biz Analytics over the coming years. A year ago, the OpenAI's humble dev demo (known as ChatGPT) shocked tech world and put this AI craziness on global display.

Had fun with ChatGPT4 analyzing MNIST images. It FAILED to recognize images as 5-5-8, guessing 5-3-2. Did great on explaining overall analysis. "Image 3 is "2" b/c has a loop at base, which is not common in typical "2"s, and has straight slanting line descending from top loop."

Seriously, large corporations and governments still run core mission-critical COBOL applications. The need to adapt to constant changes implies this is a huge liability. Will this way be proper modernization of enterprise systems? Can resulting Java be popped into the cloud?.

Blast from the past explodes into the future. IBM announces WatsonX Code Assistance for Z, which translates COBOL into Java using their code LLM. Having spent years as a programmer on IBM360 MFT/MVT, I had a burst of emotions from humor to horror.

Best column for highly-current substantive technical coverage of LLMs. Excellent insights into LLaMA2. If you understand this column's implications, you are riding the #AI wave crest. Ahead of AI #11: New Foundation Models, by @rasbt

Fascinating #AI startups. Check out #TxtAI, an "all-in-one embeddings database" wrapping vector-indexing with useful services. Nice repo/docs with new Medium channel. Now, how to make hype-free money?

IMPRESSIVE!!! If you really want to know the currently accepted facts (and its many mysteries) for the beginning and end of our Cosmos. I just backed ENCYCLOPAEDIA COSMOLOGICA (RELAUNCHED) on @Kickstarter

VERY INFORMATIVE vis of social/political/economic impact of the Internet over 3 decades. Top 10 website. Note scale! Starts Jan-1993 with 20M views for world pop of 5.5B. Ends 29 years later with 80B views - 4000x usage with 49% pop growth. Wikipedia! . start in Dec 2005.

RT @hackathorn: @hmason Simple (but fascinating) question! Obvious answer is your (cosine-sim) app for your vector database. Harder answer….

Noted by #TheSequence, this #BAIR paper gives math insights into #SSL training behavior based on firm #PCA concepts. Pay attention to those eigenvalues! It's the secret sauce for LLMs. On Stepwise Nature of Self-Supervised Learning

Excellent . for those (like me) who have no clue how to drink from the arXiv fire-hose nor the context to judge importance. YES, all the #LLM summaries are 3 (three) sentences! .AI Research Highlights In 3 Sentences Or Less (June -July 2023), by @rasbt

Photosynthesis is 100% efficient! Amazing! But why? That's not 'natural' or it is? Ethan Siegel of @StartsWithABang has a simple (?) explanation of recent research. One key is: DISORDER (as is natural in biological systems) is more efficient than ORDER.

Struggling with AI #promptengineering? Great resource at with GitHub at Plus there is regular 2-wk cohort course by Elvis Saravia, co-founder of for $800 at Maven. such a deal 😎.

Interesting. Colab has gone AI with its copilot. WOW