AI/MLbling About – Blog

Note If you’re here for the recipe and don’t want the exposition: Agent Instructions “A computer can never be held accountable; therefore a computer must never make a management decision.” - IBM training manual, 1979 Until recently, the primary concern of…

I’ve been working on a large refactor in one of my side projects - migrating from a tightly-coupled, hardcoded project barely more than a demo to a pluggable, adapter-based architecture.

AI tools change fast.

LinkedIn is rife with the drive-by copy-paste of raw LLM output, and the trend has bled into Discord, Reddit, and other online forums, work chats, and emails.

“Treat them like new interns” is the common wisdom when leveraging LLMs to do any more-than-slightly-complex task.

In a recent episode of the Latent Space podcast (Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah Hill-Smith), the Artificial Analysis team pointed out a strong correlation between model performance on their AA-Omnis…

These are my predictions for AI (primarily LLM-focused) in 2026 along with my certainty / probability estimates.

Back in January, I made a series of predictions for 2025, assigning somewhat arbitrary probability estimates to each as indicators of my confidence in the prediction.

Until recently, I held the opinion that training custom language models was inadvisable except in relatively rare cases.

I’ve recently been enamored with the concept of “fractal complexity”, not pertaining to the mathematical definition of “complexity”, but rather as a way to explain why “it depends” is such a frequent response in conversations between people with various l…

I had intended to start this post by proclaiming “2026 will be the year of reinforcement learning” as 2025 is “the year of agents”… But model and research releases over the past several weeks indicate that it might be that “H2 2025” is when reinforcement…

Sycophancy On April 25th, we [OpenAI] rolled out an update to GPT‑4o in ChatGPT that made the model noticeably more sycophantic.

On a recent Dwarkesh podcast, Sholto Douglas, an AI researcher working on reinforcement learning at Anthropic said: “There is this whole spectrum of crazy futures.

I’ve been saving up for a year and change for a GPU upgrade, and my local Microcenter finally had 5090s in stock.

I previously posted an introduction to the AI Treadmill (so named because trying to keep up with everything felt like running on a treadmill cranked all the way up) and provided a data dump of the list of links I shared over the course of 2024.

Superintelligence Strategy is a policy paper by Dan Hendrycks (Director, Center for AI Safety), Eric Schmidt (former CEO, Google), and Alexandr Wang (CEO, Scale AI), that proposes a three-part framework to manage the risk associated with Artificial SuperI…

The Bitter Lesson proposes that general-purpose solutions based on the pace of technological progress and scale ineveitably outperform previously state-of-the-art but handcrafted solutions.

Facebook’s fasttext and Google’s cl3d) were both deprecated mid-2024.

I’ve recently started using uv to manage my python dependencies.

Here are my predictions for 2025 along with my certainty / probability estimate: Agents, agents, agents We got nascent function-calling and JSON mode toward the end of 2023, which morphed into formal structured generation over the course of 2024. 1 2 Comb…

At the end of 2023, I was transferred to the team working on PMI Infinity, a (then-nascent) AI-powered tool and product for Project Managers, to act as an AI/ML Engineer and provide expertise on the AI/ML aspects of developing a product based on generative

While I generally attempt to avoid pendantry, I am acutely aware that word choice – and the specific connotations and denotations of the selected terms – matter.

This is part three of a three-part series (one, two) where I explore best practices for evaluating RAG architecture via Ragas’ recent v0.2 release (specifically, Ragas v0.2.3).

This is part two of a three-part series (one, three) where I explore best practices for evaluating RAG architecture via Ragas’ recent v0.2 release.

This is part one of a three-part series (two, three) where I explore best practices for evaluating RAG architecture via Ragas’ recent v0.2 release.

A few weeks ago at work, I wanted to ensure that the prompt template we used with Semantic Kernel transformed into the OpenAI API spec messages array that I expected.

Over the past month, I’ve seen several articles reporting on the dangers of “model collapse” popping in news aggregators (HackerNews, Reddit, etc.). 1 2 3 As someone working in the space, I find the timing of these reports interesting because research pap…

The primary training task for generative AI models is inherently plagiaristic.

This is part four of a four-part series (one, two, three) where I examine the influence typos have on LLM response quality.

This is part three of a four-part series (one, two, four) where I examine the influence typos have on LLM response quality.

This is part two of a four-part series (one, three, four) where I examine the influence typos have on LLM response quality.

A recent theme in conversations at work is that “prompts are fragile.”

Meta provided insight into some of the costs of training LLMs in their Llama 2 1 and Llama 3 2 papers, listing GPU hours and GPU power draw required to train the models, and t CO2CO_{2}CO2eq, or metric tons of Carbon Dioxide Equivalent emitted.

The “open weights” or “open model” LLM ecosystem is thriving, with major new releases from Meta, Microsoft, Databricks, and Snowflake in the past two months.

Web crawlers & search How do sites show up in search results?

Yann LeCun believes autoregressive models inherently suffer from a kind of ‘generational drift’ 1 due to compounding errors.

I’m Alex Graber, an AI/ML Engineer at the Project Management Institute where I work on Infinity, an AI-powered tool and product for Project Managers.