Viewing profile — JoshCole

That is part of why https://mieza.ai/ is giving a grounding layer that is backed by game theory. Actions have consequences. Tracking decisions and their consequences is important. …

> Can you talk more about why you chose CLJ for datascience / ML. I use Python for a lot of machine learning. My vision transformers, for example, are in Python. There is a lot to …

I know others already pointed out a ton of things, but having worked with Clojure in 2016 and doing active Clojure development for my startup now I feel like I have to chime in too…

I've been obsessed with game theory for years. Started by reimplementing papers, got annoyed at how bad the tooling was, wrote my own, and somewhere along the way realized the fiel…

It is pleasantly sensible since servant leadership in a sense creates an innocence because of the incents; the underlying reality is that wisdom dwells with prudence. Principles of…

Very cool work Jan! Have you tried experimenting with ham-fisted? I've found the libraries in the techascent part of the Clojure ecosystem to be very good performance wise. Ditto f…

Lisps (like Clojure) treat code as data (lists), so you write: `(if x (y) (z))` instead of Python’s `y() if x else z()`. So the code is more concise, but does less to walk a novice…

> We are now getting an equivalent definition of what neural nets are being trained for! LLMs are trained to compress the internet as much as possible! Nice payoff. Others have als…

Chess engines cannot see like a human can. When they think they don't necessarily think using the exact same method that a human uses. Yet train a chess engine for a very long time…

You're doing this thing again where you say tons of things that aren't true. > An LLM only learns through input text. This is false. There already exist LLM which understand more t…

I don't find it reasonable that you didn't understand my corrections, because current AI already do. So I'm exiting the conversation. https://chatgpt.com/share/683a3c88-62a8-8008-9…

For an example of a reward model that doesn't include "C" explicitly consider a reward model defined to be the count of the one bits in letters in the input. It would define a rewa…

> But doesn't reward for "*C" means that "C" is in the training data? You're running into an issue here due to overloading terms. Training data has three different meanings in this…

In reinforcement learning and related fields, a _reward model_ is a function that assigns a scalar value (a reward) to a given state, representing how desirable it is. You're at li…

> Only if you create new reward models for C, the output for D will improve, and so on. Again, tons of false claims. One is that 'you' have to create the reward model. Another that…

> dependent on human curated reward models to score the output to make it usable. This is a false premise, because there already exist systems, currently deployed, which are not de…

> it can't "think" of something entirety conceptionally new, because it doesn't really "think". Hierarchical optimization (fast global + slow local) is a precise, implementable not…

They don't claim that. They say LLMs only generate text someone has written. Another way you could refute their premise was by showing the existence of AI-created programs for whic…

> LLMs can only give you code that somebody has wrote before. This premise is false. It is fundamentally equivalent to the claim that a language model being trained on a dataset: […

> Congress hasn't approved DOGE. In 2014, under Obama, the United States Digital Service was established with by Congressional appropriations with the mission to "deliver better go…

Competent companies tend to put a lot of effort into building data analysis tools. There will often be A/B or QRT frameworks in place allowing deployment of two models, for example…

The article claims as part of its argument that AI has not had algorithmic advances since the 80s. This is an exceedingly false premise and a common misconception among the ignoran…

From the Hacker News guidelines: > Be kind. Don't be snarky. Converse curiously; don't cross-examine. Edit out swipes. > Comments should get more thoughtful and substantive, not le…