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A practical reflection on why coding agents lose the thread between sessions, and why the repository itself is the right place to preserve it. I used to think the problem was memory. That was the obvious diagnosis. Every new coding-agent session started with the same ritual. Open the repository. Rea
Most of us use LLMs every day now, but if you asked the average developer what's actually happening between hitting enter and getting a response, the answer is usually some mix of "it's a neural network" and a shrug. That's fine — you don't need to know how a database B-tree works to write a query.
Microsoft just shipped MAI-Thinking-1, their first in-house reasoning model. If you've been watching the AI space, you know reasoning models — the kind that "think before they answer" — have become a battleground. OpenAI has o3, Anthropic has Claude with extended thinking, Google has Gemini's thinki
How a simple choice shapes exploration, safety, and efficiency The post The Fundamental Choice in Reinforcement Learning: On‑Policy vs. Off‑Policy appeared first on Towards Data Science.
AI researcher, entrepreneur, and investor Oren Etzioni lays out 10 commandments for AI startups — covering business models, distribution, inference costs, and avoiding dependence on any single frontier model — preceded by 10 classics that apply to startups in general. Read More
When Quilty hit the industry trades earlier this year, the AI startup promised that its tool could accurately predict a film's success just by reading the script. When people actually got a chance to experiment with Quilty's product, though, they were left skeptical. Even with all the available data
This is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. Opt in for Optimizer here. A few days ago, I walked into the basement of a midtown gym. Smoothies and healthy s
Every time your agent calls an LLM, it sends the full conversation history. Turn 20 includes turns 1–19. Turn 50 includes turns 1–49. Nobody notices because it's happening inside the agent, silently, on every single request. I noticed it while building Trooper - a Go proxy that sits between agents a
Your old laptop is powerful enough for local AI... if you temper expectations
Python tutorial for fine-tuning a Mistral Small 3.1 on an imbalanced training set to classify 15 emotions in social media communication The post How to Fine-Tune an SLM for Emotion Recognition appeared first on Towards Data Science.
Shell will use agents from C3 AI to shift from basic anomaly detection towards fully-automated predictive maintenance. The global energy giant is building on their current use of the C3 AI Reliability Suite, which already keeps tabs on more than 30,000 crucial pieces of equipment across upstream and
[[IMG: dev using AI coding tool with live web UI in background]] In AI-assisted coding, the single biggest thing holding back agent performance isn't model size or speed. It's context — and nowhere is that clearer than in user interface (UI) work. Most AI coding agents can't see what you're seeing.
Anthropic says AI now writes most of its code and runs increasingly complex research tasks, leaving people to decide which problems are worth solving.
As large language models evolve from mere chatbots into autonomous agents capable of reasoning, planning, and acting, they are beginning The post Autonomous agents have met their biggest challenge yet: The database. appeared first on The New Stack.
In Part 1 of this series, we introduced Chronos-2, a time-series foundation model. We got our hands dirty by walking through a real case study and saw what Chronos-2 can do straight out of the box, with no training. But as we noted at the end of Part 1, zero-shot isn’t always enough. In cases […] Th
When images, mosaics, and data cubes exist in abundance, but field labels are expensive, rare, and imperfect. The post Small Data, Big Maps: Training Geospatial ML Models When Samples Are Scarce appeared first on Towards Data Science.
Let me be clear about my role up front, because it matters: I didn't hand-write the code for this. I designed the system and directed it — the architecture, the decisions, the why, and the discipline of debugging it. The actual implementation was written by AI coding agents (Claude and Codex). I was
The engineer starts with architecture. The gambler starts with a prompt. I have been both. And I have watched enough codebases collapse under the weight of AI-generated confidence to know exactly where the line is. This is not a piece about whether you should use Claude Code, Cursor, or any other AI
A look at the real-world value of online graduate AI programs, combining hard data with firsthand experience of a big tech machine learning engineer The post Is an Online Master’s Degree in AI a Good Idea? appeared first on Towards Data Science.
The most consequential line in Intel’s Computex announcement was not about a chip. It was about a ratio. As AI workloads move from training to inference, the company argued, the long-standing arrangement of four GPUs to every CPU collapses towards something closer to one to one, and the processor In
