I really like this kind of experimentation. Programming languages will be soon an agent tool, not a human tool anymore. So why bother with syntax. Just the concepts represented as an AST. Maybe even lower than that
In the next version of Zerolang
Agents get closer to the compiler
Instead of making agents edit source text, then recover meaning through format/check/build/test loops
Zerolang makes the compiler's semantic graph the program
Agents query it, patch it, and get checked edits
PumpFun is regularly creating the cheap poisonous fast food like experiences that crypto is rightfully criticised for. First memecoins then this… let’s create a better future for all participants not just for selected few
In this new agentic workflows era, is there a kanban-like tool where for each column the tickets get processed by a skill and then pushed forward?
E.g. Research -> PRD -> Issues -> Dev -> QA -> Deploy
I've implemented GPT-2 on my machine. Some takeaways:
1. wow
2. impressive that a few simple concepts, in the right shape, can be this powerful
3. I still dislike python and its tooling... 🥶
I am studying token embeddings for LLMs and how we represent meaning of a word and the context of the sentence it's in. It's mind boggling to learn that we can pack so much meaning in a series of numbers, enriched, refined and summarised over multiple steps.
I will dedicate next week to go way deeper in how frontier LLMs and AI systems work, get architected and trained.
I bought this course https://t.co/2zPOZb0z9z and brewed a big jug of coffee. I am ready
@ajwarner90@rudolf6_ Agree. The price being down for so long in one reason per se. It attracts less people.
And I confirm that the fact that the only working use cases are around trading makes it a bit boring…
I want to see more fun and creative use cases
Ethereum continues shipping and making progress to be the internet and finance backbone of the future. Not that bs chain like Solana. Relentless focus on fundamentals and not yapping, sooner or later will pay off in its price.
I just released a little tool to understand if your website is getting indexed by ChatGPT, Google AI, Perplexity, etc, or if you have to update your settings. Let me know if you would like to see more data integrated
https://t.co/4PuuJcyavY
I just discovered that when my MacBook M1 has the neural engine chip drawing max current it makes a noise at 6khz (buzz).
Every time a local ai model is running, the chip is maxed out, and my Mac buzzes... 💀
Evaluation of different models for webpage threat detection completed.
gemma3:4b => good quality and fast (~2.5s)
gemma4:e2b => better quality, but too slow (~8s)
qwen2.5:3b => low quality
llama3.2:3b => lowest quality
We have a winner for a baseline machine (M1 Max).
And I am adding a debug time feature to add new cases to the eval corpus. So I can simply click a button to add the current email/message/webpage to the eval tests corpus from Juno UI (while fixing the threat levels).
It could be post-training dataset in the future
I am creating a full Swift evals suite to Juno AI defender.
I need to understand which [input preprocessing + ai model + system prompt] leads to better threat detection.
I am measuring latencies, cost of mistakes (false positives are worse than false negatives), prompt inj
Yesterday I added the ability to specify which apps you want to monitor with Juno (local ai defender). There are strong defaults ofc, but maybe I want to remove noise...