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18:31ENGemini 2.5 Pro Experimental: Coding Demos and Launch BenchmarksMatthew Berman · Forward FutureIn March 2025, Matthew Berman tests Google’s experimental model on interactive simulations and reviews its launch benchmarks, including their limits.
24:14ENGPT-4o Image Generation: Launch Demos, Editing, and LimitationsMatthew Berman, Sam Altman · Forward FutureMatthew Berman reviews OpenAI's March 2025 image-generation launch, testing text rendering, image editing, and visual consistency.
27:32ENOpenAI’s Responses API and Agents SDK: A Launch WalkthroughMatthew Berman · Forward FutureMatthew Berman reacts to a launch demonstration of web and file search, computer use, agent handoffs and tracing.
21:48ENVibe Coding With Cursor and Windsurf: Berman’s 2025 WorkflowMatthew Berman · Forward FutureMatthew Berman shares project rules, testing habits and version-control practices from early experiments with coding agents.
19:32ENGPT-4.5’s Launch: Conversational Style, Benchmarks and CostMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s February 2025 research preview, its selected demonstrations, reported evaluations and high launch pricing.
17:20ENVibe Coding a Login Page and an AI Tetris PlayerMatthew Berman · Forward FutureMatthew Berman experiments with AI-written code, iterates through failures and trains a basic game-playing agent.
17:04ENTraining AI Agents to Communicate in a Social-Deduction GameMatthew Berman · Forward FutureMatthew Berman explains Stanford researchers’ listening and speaking objectives in a simulated game inspired by Among Us.
18:05ENOpenAI’s Coding-Competition Study: o1-ioi, o3 and the Limits of the ResultsMatthew Berman, Sam Altman · Forward FutureMatthew Berman interprets OpenAI’s 2025 paper on reinforcement learning and programming contests. The results are strong on the studied benchmarks, but do not establish AGI or remove humans from model development.
15:33ENLatent Reasoning and Recurrent Depth: Scaling Compute Before the Next TokenMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines a 3.5-billion-parameter research model that repeats internal computations, and asks how it relates to language, planning and chain of thought.
21:10ENSam Altman’s 2025 AI Coding Forecast and Three ObservationsMatthew Berman, Sam Altman · Forward FutureMatthew Berman examines predictions about reasoning models, software agents and AI economics, distinguishing competitive-programming results from broader work.
24:22ENDario Amodei on DeepSeek, AI Costs and Chip Export ControlsMatthew Berman, Jonathan Ross, David Sacks · Forward FutureMatthew Berman examines the Anthropic CEO’s 2025 essay, the limited evidence behind distillation allegations and the economics of model training.
20:34ENDeepSeek R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines 2025 reactions to DeepSeek, from training efficiency and market losses to open weights, privacy and the possibility of a demand rebound.
16:45ENDeepSeek-R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines the January 2025 reaction to an open-weight reasoning model, disputed cost claims and competing views of future demand for AI chips.
15:10ENDeepSeek R1 Tested on Coding, Reasoning and Sensitive QuestionsMatthew Berman · Forward FutureMatthew Berman runs the full R1 model on cloud GPUs and tries game programming, reasoning puzzles and politically sensitive prompts.
16:25ENWhy Test-Time Compute Could Reshape AI InferenceMatthew Berman, Lisa Su, Jensen Huang · Forward FutureMatthew Berman explains how extra computation at inference can improve model outputs, and why hardware executives expect a much larger inference market.
15:06ENJensen Huang on General Robotics, AI Workers and ScienceMatthew Berman, Jensen Huang · Forward FutureMatthew Berman reviews a No Priors interview with NVIDIA’s CEO, discussing robots in existing environments, AI agents and predictions about scientific research.
27:42ENMatthew Berman on Capital, Human Ambition, and a Possible Post-AGI EconomyMatthew Berman · Forward FutureA speculative essay asks whether advanced AI could make wealth more powerful while reducing the leverage people gain from work. Berman explores its implications for mobility, institutions, and meaning.
15:34ENSam Altman on AGI and Superintelligence: A 2025 DiscussionMatthew Berman, Ray Kurzweil, Lex Fridman · Forward FutureMatthew Berman examines Altman’s statements about AGI, the singularity and possible AI-driven scientific progress.
19:06ENBuilding Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.
21:02ENReactions to OpenAI’s 2024 o3 Preview: Benchmarks, Cost and LimitsMatthew Berman · Forward FutureMatthew Berman surveys the responses to the o3 preview, from mathematical benchmarks to debates about AGI, compute and reliability.
26:23ENOpenAI’s o3 Announcement: Benchmark Gains and the Question of AGIMatthew Berman, Sam Altman, Mark Chen, Greg Kamradt, Hongyu Ren · Forward FutureMatthew Berman reviews the December 2024 o3 and o3-mini announcement, including coding, math and ARC-AGI results. He calls the results evidence of AGI, a conclusion the benchmarks alone cannot establish.
24:08ENWhat Apollo’s 2024 Scheming Tests Found in Language ModelsMatthew Berman · Forward FutureMatthew Berman reviews experiments on deceptive actions, concealment and sandbagging, with the study’s staged goals and sandbox limitations in view.
22:12ENOpenAI’s 2024 Canvas Update: Writing, Python Execution and Custom GPTsMatthew Berman, Kevin, Lee, Alexi · Forward FutureMatthew Berman reviews a launch demonstration of collaborative editing, an in-canvas Python debugging loop and Canvas support for custom GPTs.
27:54ENAI News in December 2024: Genie 2, World Models, MCP and New AI ReleasesMatthew Berman · Forward FutureMatthew Berman surveys early interactive world models, voice and video tools, QwQ, distributed training and Amazon’s Nova announcements.
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