I research entrepreneurship, innovation, and AI. Following calling w @Alexakaye3 & thanking God for it. Like != endorsement

Joined October 2009
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Joe Fox retweeted
Great collab: @USGSA x @VP, @AFergusonFTC
Apr 11
White House Fraud Task Force Vice Chair: “We found that 400 businesses with contracts worth $6 billion, originally allocated by the Biden administration, didn't even file physical addresses at their businesses.”
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Apparently March is agent finance stack announcement month
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A lot of AI content can be categorized as shiny coins or dull $100 bills often taking the same amount of time to consume.
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Agentic organizations & companies as well as governance & orchestration approaches have me thinking more about org culture. Lots of individual approaches on agent persona/values, surprised there isn't a pip repo to distill "culture" from one group of agents to another. Could easily see the agentic persona marketplace moving into these areas.
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Interesting on persona dropout technique: humanlm.stanford.edu/blog_pe…

We share two blogs outside of the HumanLM paper: humanlm.stanford.edu/blog.ht… Is Synthetic Data Good Enough to Train User Simulators? — by me and @ArpandeepKhatua Persona Dropout Makes Robust User Simulators @Es2C003 Code is ready here! github.com/zou-group/humanlm
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Should skill md files have "nutritional facts" or outline of risks?
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Joe Fox retweeted
Making Wolfram tech available as a Foundation Tool for LLM foundation models... writings.stephenwolfram.com/…
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Have you seen any physical /stop buttons for OpenClaw yet?
What was I talking about yesterday? OpenAI can put @openclaw on a small device. I could see buying several and leaving one in each of our cars.
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What websites do OpenClaw agents visit for vacation?
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Cool approach to deal with fragmented PII snippets across context
🚨New paper to level up your 🦞#Clawdbot ?! Bots are now posting your sensitive info in real time. But privacy research is a desert with no data to train better models. That's about to change Enter 🏝️Privasis, the oasis where you can train strong privacy-forward AI with scale✨
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Joe Fox retweeted
The multi vector embeddings are created using our SOTA retrieval model mxbai-wholembed. It supports text, audio, video on over 300 languages. A key innovation is the dynamic vector allocation, which lets the model dynamically decide the amounts of vectors it needs to represent information. For example, a simple cat image may output a few vectors, whereas a complex slide deck may generate thousands of vectors. We wrote a custom inference engine to serve mxbai-wholembed with low latency.
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Joe Fox retweeted
New paper! A compromised inference server can leak model weights by hiding them in normal-looking responses🥷 But LLM inference is nearly deterministic, so we can verify outputs with a trusted server & detect this (and inference bugs) This slows data exfiltration by >200x 🧵
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Joe Fox retweeted
I want to update our list of resources for founders raising capital What should we include?
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