muckrAIkers

In this episode, Jacob and Igor break down the DoD vs. Anthropic standoff, tracing how Claude's use in military operations led to Anthropic being designated a supply chain security risk. Perhaps more importantly, why did Anthropic choose to take a stand now, and what can that tell us about the corporations behavior moving forward. The investigation is used as a case study in how to read the real motivations behind big inst...

This week, Jacob and Igor dissect the "mythical AI bear," the strawman version of AI criticism that gets thrown around in tech discourse. Working through a viral blog post that typifies the genre, they examine how legitimate concerns about code quality, labor displacement, intellectual property, and the erosion of craft get flattened into caricature. Plus: Sam Altman writes ten paragraphs about how unbothered he is by an a...

We're talking about developments in AI while those in power have unapologetically revealed their true fascist intensions; are we spending our time in the right way? Igor and I discuss the importance of shining a light on the techno-authoritarians who have played a very significant role in current state-of-the-world.

While we discuss the murders of Nicole Good and Alex Pretti during this episode, it's important that we also ...

Igor shares a significant shift in his perspective on AI coding tools after experiencing the latest Claude Code release. While he's been the stronger AI skeptic between the two of us, recent developments have shown him genuine utility in specific coding tasks, but this doesn't validate the hype or change the fundamental critiques.

We discuss what "rote tasks" are and why they're now automatable with enough investment, the d...

OpenAI is pivoting to porn while public sentiment turns decisively against AI. Pew Research shows Americans are now concerned over excited by a 2:1 margin. We trace how we got here: broken promises of cancer cures replaced by addiction mechanics and expensive APIs. Meanwhile, data centers are hiding a near-recession, straining power grids, and literally breaking your household appliances. Drawing parallels to the 1970s AI ...

Jacob and Igor argue that AI safety is hurting users, not helping them. The techniques used to make chatbots "safe" and "aligned," such as instruction tuning and RLHF, anthropomorphize AI systems such they take advantage of our instincts as social beings. At the same time, Big Tech companies push these systems for "wellness" while dodging healthcare liability, causing real harms today We discuss what actual safety would lo...

We dig into how the concept of AI "safety" has been co-opted and weaponized by tech companies. Starting with examples like Mecha-Hitler Grok, we explore how real safety engineering differs from AI "alignment," the myth of the alignment tax, and why this semantic confusion matters for actual safety.

• (00:00) - Intro
• (00:21) - Mecha-Hitler Grok
• (10:07) - "Safety"
• (19:40) - Under-specification
• (53:56) - This time isn't ...

In this episode, we redefine AI's "reasoning" as mere rambling, exposing the "illusion of thinking" and "Potemkin understanding" in current models. We contrast the classical definition of reasoning (requiring logic and consistency) with Big Tech's new version, which is a generic statement about information processing. We explain how Large Rambling Models generate extensive, often irrelevant, rambling traces that appear to ...

In this episode, we break down Trump's "One Big Beautiful Bill" and its dystopian AI provisions: automated fraud detection systems, centralized citizen databases, military AI integration, and a 10-year moratorium blocking all state AI regulation. We explore the historical parallels with authoritarian data consolidation and why this represents a fundamental shift away from limited government principles once held by US conse...

Jacob and Igor tackle the wild claims about AI's economic impact by examining three main clusters of arguments: automating expensive tasks like programming, removing "cost centers" like call centers and corporate art, and claims of explosive growth. They dig into the actual data, debunk the hype, and explain why most productivity claims don't hold up in practice. Plus: MIT denounces a paper with fabricated data, and Grok r...

DeepSeek has been out for over 2 months now, and things have begun to settle down. We take this opportunity to contextualize the developments that have occurred in its wake, both within the AI industry and the world economy. As systems get more "agentic" and users are willing to spend increasing amounts of time waiting for their outputs, the value of supposed "reasoning" models continues to be peddled by AI system develope...

DeepSeek R1 has taken the world by storm, causing a stock market crash and prompting further calls for export controls within the US. Since this story is still very much in development, with follow-up investigations and calls for governance being released almost daily, we thought it best to hold of for a little while longer to be able to tell the whole story. Nonetheless, it's a big story, so we provide a brief overview of...

Chris Canal, co-founder of EquiStamp, joins muckrAIkers as our first ever podcast guest! In this ~3.5 hour interview, we discuss intelligence vs. competencies, the importance of test-time compute, moving goalposts, the orthogonality thesis, and much more.

A seasoned software developer, Chris started EquiStamp as a way to improve our current understanding of model failure modes and capabilities in late 2023. Now a key contra...

What happens when you bring over 15,000 machine learning nerds to one city? If your guess didn't include racism, sabotage and scandal, belated epiphanies, a spicy SoLaR panel, and many fantastic research papers, you wouldn't have captured my experience. In this episode we discuss the drama and takeaways from NeurIPS 2024.

Posters available at time of episode preparation can be found on the episode webpage.

EPISODE RECORDED 2...

The idea of model cards, which was introduced as a measure to increase transparency and understanding of LLMs, has been perverted into the marketing gimmick characterized by OpenAI's o1 system card. To demonstrate the adversarial stance we believe is necessary to draw meaning from these press-releases-in-disguise, we conduct a close read of the system card. Be warned, there's a lot of muck in this one.

Note: All figures/tab...

While on the campaign trail, Trump made claims about repealing Biden's Executive Order on AI, but what will actually be changed when he gets into office? We take this opportunity to examine policies being discussed or implemented by leading governments around the world.

• (00:00) - Intro
• (00:29) - Hot off the press
• (02:59) - Repealing the AI executive order?
• (11:16) - "Manhattan" for AI
• (24:33) - EU
• (30:47) - UK
...

Multiple news outlets, including The Information, Bloomberg, and Reuters [see sources] are reporting an "end of scaling" for the current AI paradigm. In this episode we look into these articles, as well as a wide variety of economic forecasting, empirical analysis, and technical papers to understand the validity, and impact of these reports. We also use this as an opportunity to contextualize the realized versus promised f...

October 2024 saw a National Security Memorandum and US framework for using AI in national security contexts. We go through the content so you don't have to, pull out the important bits, and summarize our main takeaways.

• (00:48) - The memorandum
• (06:28) - What the press is saying
• (10:39) - What's in the text
• (13:48) - Potential harms
• (17:32) - Miscellaneous notable stuff
• (31:11) - What's the US governments take on A...

Frontier developers continue their war on sane versioning schema to bring us Claude 3.5 Sonnet (New), along with "computer use" capabilities. We discuss not only the new model, but also why Anthropic may have released this model and tool combination now.

• (00:00) - Intro
• (00:22) - Hot off the press
• (05:03) - Claude 3.5 Sonnet (New) Two 'o' 3000
• (09:23) - Breaking down "computer use"
• (13:16) - Our understanding
• (...