PhD in business analytics. Ensuring that Deep Learning (AI) systems are manageable and responsible at scale, while "wandering in latent space".
Boulder, Colorado USA
Joined July 2007
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The capstone project for Google 5-Day Agent Intense was a kick because I teamed with my son Eric Hackathorn on a "AI-for-Good" Zyra project to streamline workflow utilization of NOAA's massive scientific data sets.
github.com/NOAA-GSL/zyra
I got my Kaggle certificate for the Google 5-Day Agent Intensive course and capstone project. I was impressed by Google's thoughtfulness in their Agent Developer Kit (ADK) towards enterprise-level agentic implementations.
kaggle.com/learn-guide/5-day…
Interesting analyst briefing with Salesforce/Tableau on their evolving analytic semantic models. Nontrivial work to connect classic data semantics with 'GenAI ready' semantics so that humans and AI agents can properly collaborate. OpenAI, Google AI, & the like should take note.
Check out my latest article: Decision Support to Organizational Semantics... summarizes a journal paper on research issues for AI-assisted decision support in organizations.
linkedin.com/pulse/decision-… via @LinkedIn
MIT Technology Review just posted insightful article on "Tech Industry Can't Agree on What Open-Source AI Means".
lnkd.in/g5t44jaw
This has been bugging me for months: What does it mean? Does it matter? What are implications for “ethical, trustworthy, or responsible” AI?
I recommend study of excellent in-depth paper by Sarah West of AI Now Institute. lnkd.in/gqcuEEyw
The article confirms the chaos reigning within the entire industry and concludes with slim hopes placed on OSI, RAIL, ImpACT Licenses, and Tidelift.
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.
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?
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."
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.
newsroom.ibm.com/2023-08-22-…
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 magazine.sebastianraschka.co…
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? github.com/neuml/txtai
medium.com/neuml/introducing…
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 kickstarter.com/projects/cos…
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.
Richard Hackathorn retweeted
Simple (but fascinating) question! Obvious answer is your (cosine-sim) app for your vector database. Harder answer is how you understand structural relationships (manifolds?) among object embeddings, especially within local neighborhoods. Smashing 1000s dim into 2? 👎
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 bair.berkeley.edu/blog/2023/… gitlab.com/generally-intelli…
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 open.substack.com/pub/sebast…