shaburn

thats what the auditors that charge a fortune are for

You should now assume your sources are compromised if you did not expect this

Would be great to have a fixed blockchain based event log, ideally encrypted.

How would you score your ability to negotiate 1 to 10 (10 as the best)?

Which books? Where do I find them exactly? More quantitative than qualitative. More like SEC data.

My brain.

I mostly just want to know how much water/nutrients to provide it and when.

Current Admin = EA ... "'The speed of SEC rule-making has created difficulties for firms. The IAA said the SEC should take a step back from that proposal and work with the industry. “The pace of the rule-making and the complexity of the proposals and how they may interact with each other puts a large burden on the compliance department to be able to practice in a way that is coherent,” Ropes & Gray’s Longo said.' "

Visualization never seems to get the credit due in software development. This is amazing.

I beleive the model bias is highly influenced by the modelers. See Grok and OpenAI.

LlamaIndex, HuggingFace, LangChain, and Ludwig are functioning as partial proxy aggregators of what is working and working better than alternatives. Most people in this space have multiple models for virtually every step in their heads. You cannot and should not process them. Thus you need aggregation and filtration on some objective(s) and presumptions with a purpose or you're a boat on a turbulent sea.

One simple tool I use to evaluate is how easy is it to spin up a working demo, in isolation or context of other tools, to show the maturity of thought on the idea moving to application. If there is no benchmark on output(s) before you start that is more science/fantasizing than business. but maybe that's your goal, just don't delude yourself in what you're doing. I also look up project leads on Linkedin and such since these things require push and without a good promoter, usually don't pan out(see crypto for example).

Buried lead: I've built a few tools allowing me to parse the tree and graph structures of new projects in charts/schemas to get quick visuals for myself and the LLMs I use to code. Additionally, I have built tooling to test rapidly. For if everything is dynamic, optimizing measurement is quite valuable in and of itself.

Why will function names and variables be named better? Will this also apply to the better code bases?

I think structure will shrink and simplify to fit context window token limits at the expense of developer(human) experience and developer bias.

Problem: How do I give an LLM context of a code repo with a limited token window? Solution: Top-down tree-like map parsing files

I am not referencing republishing the output results. That is a seperate act entirely. There are countless examples, particularly in regulated usecases, where threads are audited. Thus, who is liable for the output of the LLM in those threads?

I don't understand how a user will be liable when they are receiving non-deterministic outputs and have no objective way to know or control what they receive.

There exists legal precidents for all other forms of software and content production. Why is this different?

My primary question is from a legal standpoint, partially in response to new US regulation coming online.

GPT-4 with Web Browsing: Co-Founder vs LLMs General then Specific Situation...

____________ General... Advantages:

Complementary Skills: Co-founder: 15 LLM/Agents: 0 Investor Confidence: Co-founder: 15 LLM/Agents: 0 Decision Making and Strategy: Co-founder: 10 LLM/Agents: 0 Moral Support and Resilience: Co-founder: 10 LLM/Agents: 0 Networking: Co-founder: 10 LLM/Agents: 0 Liability and Responsibility: Co-founder: 5 LLM/Agents: 0 Customization and Creativity: Co-founder: 10 LLM/Agents: 0 Downsides:

Conflict: Co-founder: 0 LLM/Agents: 10 Equity Dilution: Co-founder: 0 LLM/Agents: 10 Speed of Decision Making: Co-founder: 0 LLM/Agents: 5 Operational Complexity: Co-founder: 0 LLM/Agents: 5

_____________ Now Specific situation of prospective co-founder is unknown, the Founder is a repeat Founder with domain expertise and technical talent with a very large network. And the LLMs have been tailored and are part of the company offering...

Advantages:

Complementary Skills: Co-founder: 5 LLM/Agents: 10 Investor Confidence: Co-founder: 5 LLM/Agents: 10 Decision Making and Strategy: Co-founder: 5 LLM/Agents: 10 Moral Support and Resilience: Co-founder: 5 LLM/Agents: 0 Networking: Co-founder: 0 LLM/Agents: 0 (Assuming the repeat Founder’s large network suffices) Liability and Responsibility: Co-founder: 2 LLM/Agents: 3 Customization and Creativity: Co-founder: 5 LLM/Agents: 10 Downsides:

Conflict: Co-founder: 0 LLM/Agents: 10 Equity Dilution: Co-founder: 0 LLM/Agents: 10 Speed of Decision Making: Co-founder: 0 LLM/Agents: 10 Operational Complexity: Co-founder: 0 LLM/Agents: 5

I am. And it is the best experience I've had so far, including having worked with technical founders from top schools and 8 figure exits.

Only hundreds of billions at stake if successful.

Your Uber/AirBnB/Wework all have physical base units with ascending costs due to inflation and theoretical economies of scale.

AI models have some GPU constraints but could easily reach a state where the cost to opperate falls and becomes relatively trivial with almost no lowerbound, for most use cases.

You are correct there is a race for marketshare. The crux in this case will be keeping it. Easy come, easy go. Models often make the worst business model.

This will unlock a ton of Enterprise use cases. I have met with a number of enterprises that have a hard no on sending much of their data into OpenAI, even on Azure. I think this will persist as the brand faces many hurdles with respect for IP, in public perception.

Then what are the comp sci departments screening for and why?

No. And I beleive there is a ton of product to be built to account specifically for this in big systems.

I started on this 4 weeks ago on my own but haven't published.

Postgres and Mongo support it. ElasticSearch incorporates vector search. I have failed to identify an objective difference(beyond marketing nomeclature) between any pure play vector solution after exaustive research.

That costs less than transportation to many doctors required for insurance approvals.

Really curious how a profitable industry like medical research ranks against less profitible.