This article is a record of my own automated trading bot failures and a simulation using Python. The paper (simulated) results cover only about two weeks, and I cannot claim to have skill or that it ...
I challenged myself to adapt Edogawa Ranpo's debut work, 'The Two-Sen Copper Coin,' into a 7-page manga using AI.My partner for this task was Claude Code. I used NotebookLM and Gemini for reading the ...
Trades require timestamp, ingested_at, price, size, and exactly buy or sell. The window is (decision-window, decision] by event time, with receipt at/before decision. The caller supplies one asset, a ...
Article by Shenchao TechFlowNo training required, no data needed, no gradient descent.Researchers at MIT fed the weights of ...
XDA Developers on MSN
My RTX Spark laptop still doesn't have Copilot+ features, so a local LLM on the same machine built its own from one prompt
It called it "Spark Copilot", and it works similarly to the real thing.
A Kaggle notebook extending the Duck harness with a persistent Python interpreter for each game level, an offline CPython 3.12 runtime, and lightweight execution diagnostics. The agent observes a game ...
In the strongest example of "weight space programming", as the technique is called, Astra’s intervention raised Qwen3.5-0.8B’s MATH-500 score from 7.9% to 48.1% while touching approximately 0.016% of ...
North Korean hackers stole $6.43 billion from Binance in the largest crypto theft on record, while Chinese state actors built rotating relay networks and attackers poisoned trusted software extensions ...
Discover how Open Cosmos connects Earth observation, onboard processing, and satellite communications to turn orbital data ...
Put AI to work before your day begins with automated research, prepared drafts, task tracking, and feedback that improves future work.
A new exploit for the Nintendo Switch 2 uses the Switch 1 edition of Sid Meier's Civilization VII as an entry point.
Astra identifies game policies from raw weight matrices and fixes reasoning loops in Qwen3.5-0.8B by editing 0.016% of parameters, lifting MATH-500 scores from 7.9% to 48.1% without training loops.
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