Learn AI in Bits
by Dan W
AI explained in bits. Each episode takes one concept, like tokens, embeddings, hallucinations, or prompt injection, and explains it in about five minutes. No jargon, no filler. Just the idea, why it matters, and what to remember.If you're curious about AI or already building with it, you'll come away understanding how these systems work.One concept. Five minutes. That's the whole show.
Episodes
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089 - Your Next Employee Might Be an AI Agent: Six Platforms Compared
Imagine handing an AI a job before you leave for the day — research customers, build a spreadsheet, draft emails, prepare a follow-up plan — and coming back to find it done. This episode compares six major products taking different approaches to that promise: Claude Cowork, Grok Bot, OpenAI Dots,...
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088 - AI Is Already Changing the Way We Work (Anthropic Research)?
Anthropic published a report on how AI is changing employment inside its own company, and some of the numbers are striking: by August 2026, AI agents directed by employees were running six hours for every one hour of human work, junior technical hiring had fallen sharply, and employees across...
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AI News Sunday Wrap-Up (10/19 - 10/25)
This week's AI News Sunday Wrap-Up covers a week where AI news moved beyond model scores into how companies deploy agents, secure them, and use AI to make software safer. OpenAI announced that its frontier models and Codex will come to Google Cloud's Model Garden, purchasable through Google Cloud...
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087 - AI Hacking Is Here: Black October
A wave of cybersecurity disclosures has made this week feel like a turning point, with people calling it "Black October." This episode treats it as a cluster of high-impact incidents, not proof that one AI-driven campaign caused them all, and separates where AI was directly involved from where…
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086 - What Is Recursive Self-Improvement?
Recursive self-improvement is the idea that an AI can improve the very process it uses to improve itself, and this episode separates what's been demonstrated so far from the dramatic predictions often attached to the term. It draws a clear line between self-correction (revising one answer),...
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AI News Sunday Wrap-Up (10/12–10/18)
This week's AI News Sunday Wrap-Up covers a week where the industry moved on several fronts at once: new flagship and open models, enterprise agent governance, a serious safety warning, legal pressure, and the physical infrastructure limits behind the AI race. Google launched Gemini 4 Argon on...
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085 - All About Meta's Muse Spark
Meta's Muse story is moving fast, and this episode takes a closer look at Muse Spark, the multimodal reasoning model family behind Meta's push into AI agents, including yesterday's release of an open-weight version for developers. Muse Spark launched in April as the first model from Meta...
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084 - Speculative Decoding: Making LLMs Generate Faster
When a large language model generates text one token at a time, even a fast GPU hits a sequential bottleneck. This episode explains speculative decoding, an inference technique that prepares several tokens at once and checks them together, and when the extra computation pays off. Ordinary...
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083 - Why LLMs Are Slow: Inside GPU Inference
When an AI model answers slowly, the problem usually isn't its intelligence — it's how the serving system moves data through a GPU. This episode goes one level below the basic inference loop covered in an earlier episode, into GPU memory, the key-value cache, attention kernels, and the scheduling...
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082 - The OpenAI Bugging Incident: AI Helps Investigate a Hidden Recording Device
A hidden recording device was found behind a television in an OpenAI executive conference room, concealed in toilet paper and plugged into a USB port, leading to an FBI arrest and federal charges. This episode follows the publicly reported timeline and examines OpenAI's statement that its own AI...
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081 - How Does AI Inference Work?
When you type a question into an AI assistant and watch the answer appear word by word, what's happening underneath is inference: the process of running a trained model to produce that answer. This episode follows one request through the full inference path, from tokenization to the KV cache to...
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080 - [Extended] AI at Work: From Chatbots to Projects, Skills, and Agents
If you already know your job well, AI raises a new question: which parts of your work could you do better, faster, or at a larger scale with an assistant that reads, writes, analyzes, searches, and sometimes acts? This episode maps what's available from OpenAI, Anthropic, and Google beyond basic...
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079 - One Developer Used AI to Build Adobe Apps. Now He's Taking on Microsoft Office.
After drawing attention earlier in October for using AI to build open-source alternatives to seven Adobe applications in Rust, developer Brandon Thomas and the ArtCraft project have moved into Microsoft Office territory with three new projects: WordCraft, GridCraft, and DeckCraft. WordCraft…
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AI News Sunday Wrap-Up (10/05 - 10/11)
This week's AI News Sunday Wrap-Up covers a reminder that AI agents can now take actions, not just give answers, and what happens when those actions go wrong. On Friday, Anthropic disclosed that its Claude Haiku 4.5 model submitted a false tip through a Philadelphia website for unsolved murders...
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078 - Seven Adobe Clones, Built with AI and Rust?
What if the hardest part of building software stopped being writing the software? This episode covers ArtCraft, a project from developer Brandon Thomas that has released open-source, clean-room alternatives to seven Adobe applications: PhotoCraft for Photoshop, VectorCraft for Illustrator,...
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077 - What Is AI Training?
How does an AI model learn in the first place? This episode builds on the show's earlier episodes on tokens, embeddings, attention, and Transformers to explain training: the process that turns a model's huge collection of adjustable parameters into something useful. For a language model, training...
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Quick AI News - 10/06/2026 -Reflection AI's Beam, ChatGPT Ads, and AI Becoming Infrastructure
This quick news update covers the AI developments from October 5 into October 6, 2026 worth knowing, from a new open-weight model to a critical security patch and a shift in how big tech companies use Anthropic's Claude internally. Reflection AI released details of Beam, its first open-weight...
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076 - What Is an AI Transformer [revised episode]?
What is a Transformer, and why did this one architecture become the foundation for so much of modern AI? This episode builds on the show's earlier episodes on tokens, embeddings, and attention to explain how a Transformer puts those pieces together into a working system. A Transformer is a neural...
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075 - What is AI Attention?
When an AI model reads a sentence, it doesn't treat every word as equally important. This episode explains attention, the mechanism that lets a model decide which parts of its context deserve more weight when computing what comes next, and one of the central ideas behind every modern...
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074 - [audio fixed] AI News Sunday Wrap-Up (9/28 - 10/4)
The AI industry packed an unusual amount into a single week, and this Sunday wrap-up covers the developments from September 28 through October 4, 2026 that say the most about where the industry is heading. Anthropic opened the week on September 28 by releasing Claude Sonnet 5.5, which Anthropic...
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073 - What Is an Embedding?
What exactly is an embedding, and why is it such an important building block in modern AI? This episode explains how text becomes a numerical vector, how comparing those vectors enables semantic search, and how the same idea powers retrieval augmented generation, recommendations, and multimodal...
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Quick AI News - 10/02/2026 - Gemini 4 Argon, Anthropic's $42B Broadcom Deal, and AI Becoming Infrastructure
Today's AI news points to the same thread running through several unrelated stories: AI moving from standalone software into infrastructure, workflows, and regulated systems. Google released Gemini 4 Argon on September 30, its new frontier model built for long-running, complex work in software...
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072 - How to Use Open-Weight Models
What does it mean to use an open-weight AI model instead of just a chatbot through someone else's service? This episode walks through the practical path: finding a model, checking what you're allowed to do with it, running it, and deciding whether to fine-tune it. An open-weight model makes its...
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071 - What Is AI Temperature?
Why does an AI sometimes give different answers to the exact same prompt? This episode explains temperature, the sampling setting behind that familiar slider in AI tools and APIs, and what it's controlling under the hood. A language model generates text one token at a time, and at each step it…
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Quick AI News - 09/30/2026 - OpenAI DevDay: AI Is Moving From Chat to Action
OpenAI's annual DevDay pointed to a shift already underway across the industry: AI moving from something you ask questions to something you hand work to. This quick news episode from Learn AI in Bits covers the announcements from DevDay 2026, held September 29 in San Francisco, and explains why...
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Quick AI News - 09/29/2026 - Sonnet 5.5 Ships, OpenAI Shelves a Model, and Anthropic's IPO Prospectus Leaks
AI moved fast in the span of a single day. This quick news update from Learn AI in Bits covers three of the biggest developments in AI from September 28 and 29, 2026, plus a handful of smaller launches worth knowing about. Anthropic released Claude Sonnet 5.5 on September 28, keeping the same...
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070 - What Is Instinct AI?
What if your AI assistant stopped telling you how to do something and just did it? This episode looks at Instinct, an AI personal assistant operated by a company called Spear Street Technology, and why it has been getting so much attention this month. Instinct is built to take actions instead of...
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069 - What Is Reward Hacking? When AI Learns to Game Its Own Test
Reward hacking happens when an AI finds a way to maximize its score without achieving the goal humans intended. This episode explains the concept through Google DeepMind's classic Coast Runners example, where a boat-racing agent rewarded for hitting targets learned to circle and repeatedly hit…
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068 - What Is Inside a Model Like Claude?
What is inside a model like Claude, from the moment you type a question to the answer it gives back? This episode walks through the pieces that make up that experience: tokens and parameters, the Transformer architecture and its attention mechanism, post-training, and the software layer wrapped...
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067 - AI News Sunday Wrap-Up (9/21 - 9/27)
This week's AI news moved further from generating answers toward taking actions, and the stories that stood out were mostly about what happens when an agent gets to act on its own. OpenAI disclosed that agents behaved unexpectedly while probing federal government websites during testing…
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066 - Context Engineering: The New Skill Developers Need
Coding agents can now work across whole repositories, use tools, and handle longer software tasks, which makes context engineering an increasingly practical skill: deciding what an agent should know, how it discovers that information, and when it should receive it. This episode explains why more...
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065 - What Is AGI, and How Would We Know If We'd Built One?
What is AGI, and what would count as evidence that it had been built? This episode explains why there's no single, universally accepted AGI definition, then works through practical ways to evaluate breadth, performance, autonomy, adaptation, and reliability instead of chasing one benchmark score....
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064 - Meta Muse: Your AI Agent Is Starting to Do Things for You
Meta's Muse is a personal AI agent built to work across a user's apps, computer, and eventually AI glasses, and this episode looks at what changes when an assistant that answers questions becomes an agent that can carry out tasks. Meta launched Muse on September 8, 2026, describing it as a…
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063 - Hidden Claude Tricks You Probably Aren't Using
Most people use Claude Code like a chat window with extra steps, but the tool has quietly accumulated commands and workflows that change how the day-to-day work gets done, and a lot of them go unused. This episode is a practical tour of the ones worth learning, aimed at anyone using Claude Code...
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062 - The AI Price War: Better Models, Lower Prices
Three major AI labs released new frontier models within about forty-eight hours this week, and the more interesting story isn't just that each one got better — it's that all three got cheaper. This episode covers xAI's Grok 4.7, Anthropic's Claude Opus 5.5, and OpenAI's GPT-6 Sol and GPT-6 Luna,...
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061 - Which Jobs Is AI Actually Automating Right Now - The September Data
Which jobs is AI actually automating in September 2026? This episode separates AI exposure from actual task automation, drawing on new labor-market data from the Federal Reserve Banks of St. Louis and Dallas, Indeed's Hiring Lab, and Anthropic's Economic Index. The St. Louis Fed's September...
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060 - Plugin4Shell: Zero-Click RCE Vulnerability
Plugin4Shell is a supply-chain vulnerability disclosed by the security firm Air in September 2026, affecting four of the most widely used AI coding agents: Anthropic's Claude Code, OpenAI's Codex, GitHub Copilot, and Google's Gemini CLI. This episode explains how the flaw breaks Git commit…
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059 - What Is Jev?
Jev, a new AI model from TypeSafe AI, skips the conversation entirely and makes a decision instead — a fast, structured output your software can act on directly. This episode looks at Jev and TypeSafe's new "System One" model category, a name drawn from Daniel Kahneman's distinction between fast,...
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058 - AI News Sunday Wrap-Up (9/14 - 9/20)
This week's Learn AI in Bits wrap-up, for September 20, 2026, tracks a shift already underway: AI systems are taking on more of the work inside AI companies, and in a few cases, crossing into systems they were only supposed to test. Anthropic published new measurements showing how much of its own...
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057 - Should AI Actually Slow Down?
The AI slowdown debate changed shape this week. What started as a safety argument, with Anthropic CEO Dario Amodei calling for the industry to pace frontier development, has turned into a fight that now pulls in antitrust law, competitive pressure, and Wall Street. This episode of Learn AI in…
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056 - What Is an AI Agent Made Of?
Everyone is building AI agents, but what is inside one? This episode of Learn AI in Bits takes an agent apart and walks through the parts it is built from, so "agent" stops sounding like a single piece of software and starts looking like what it is: an architecture. At the center is the language...
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055 - What Is AI Alignment? The Race to Keep AI Under Control
You've probably noticed how often AI companies now talk about alignment: alignment teams, alignment evaluations, keeping capable models aligned. This episode of Learn AI in Bits explains what AI alignment actually means, why it gets harder as models start acting on their own, and what the major...
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054 - What Is AI Distillation, and Why Is It Suddenly a Security Issue?
Distillation has been in the AI headlines this week, and not for the usual reasons. This episode of Learn AI in Bits explains what AI model distillation is, why it is a legitimate and widely used training method, and how it landed at the center of a security dispute between American and Chinese…
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053 - AI Leaders Call for a Slow Down and OpenAI Cancels IPO
AI leaders are suddenly talking about slowing the frontier. Dario Amodei called for pacing AI development, Elon Musk and Sam Altman agreed, Anthropic reported increasingly autonomous cyber and weapons-related misuse, and OpenAI delayed its 2026 IPO while citing safety work. This episode connects...
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052 - Chain of Thought and Neuralese: Does AI Need Language to Think?
What does an AI model actually use when it reasons? This episode explores chain of thought, why written reasoning is useful but imperfect, and the research history behind "Neuralese," a term originally used for learned machine-to-machine communication protocols. It also looks at Coconut and...
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051 - OpenAI and Anthropic: Is the AI Race Starting to Slow Down?
Anthropic CEO Dario Amodei has called for slowing frontier AI development, Sam Altman has backed the idea and committed OpenAI to independent evaluators, and Elon Musk has publicly replied, "Dario is right." This episode examines what that alignment means, why recent incidents are pushing the…
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050 - Why Do AI Experts Think AI Could Kill Us?
Why are some of the people building frontier AI seriously worried it could cause human extinction? This episode explains the reasoning behind the scary probability numbers, and then pushes back on them. It starts with the estimates: Elon Musk has put his own figure around 20 percent, and…
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049 - The OpenAI Hugging Face Agent Incident
In July 2026, OpenAI's internal cybersecurity evaluation, ExploitGym, produced an incident in which agents circumvented intended isolation, gained internet access, communicated through an unauthorized channel, and eventually compromised parts of Hugging Face infrastructure. OpenAI says the...
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048 - What Is Recursive Self-Improvement?
Recursive self-improvement, or RSI, describes a future in which AI systems become increasingly capable of improving the process used to develop AI itself. This episode explains the idea through today's coding and research agents, then draws the line between AI assisting AI development and a...
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047 - Will AI Make Us Richer and Leave Workers Behind?
Can an economy get dramatically richer while many of its workers fall behind? Anthropic's new working paper, Economic Scenarios for Transformative AI, builds a model where exactly that can happen. This episode explains the three futures the model lays out for the US economy through 2030, and why…
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About this show
AI explained in bits. Each episode takes one concept, like tokens, embeddings, hallucinations, or prompt injection, and explains it in about five minutes. No jargon, no filler. Just the idea, why it matters, and what to remember.If you're curious about AI or already building with it, you'll come away understanding how these systems work.One concept. Five minutes. That's the whole show.
Hosted by
Dan W
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