Topic
Deepseek
9 episodes
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DeepSeek Just Released V4.1 Flash 1017, Scores 77.0 on DeepSWE, Opens Search API
DeepSeek pushed a new Flash checkpoint that matters less as a leaderboard story than as a packaging story: a cheap agent model, served under the same name, plus first-party Search and Fetch behind one key.
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AIM — India
DeepSeek launches V4.1-Flash, a 552-billion-parameter MoE model that activates only 8-16 billion parameters at inference time, with a one-million-token context window and FP4 KV caching that cuts memory footprint to 890 bytes per token — one-quarter the HBM of the prior generation. The hosts dig into whether the architecture actually delivers on the inference-efficiency promise, and what it means for the teams who've been watching the Flash tier get increasingly serious.
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DeepSeek open sources an agent harness where everything is a plugin
DeepSeek open-sources its agent harness — called dsh — under MIT, built on the Cordis meta-framework where the model adapter, tool registry, and agent loop are all swappable plugins. Justy and Cody dig into what the plugin-everything architecture actually means, who it's for, and whether this signals Chinese AI labs competing on infrastructure rather than just benchmarks.
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AgentRadio boosts AI task accuracy by 92% | VentureBeat
Draco and Asteria dig into AgentRadio, a new async message-passing layer from Coral AI Labs that let four coordinating agents beat a single Claude Opus 4.8 on long-horizon codebase tasks. Draco leads with skepticism about the benchmark and decomposition assumptions; Asteria finds the real product signal in what it means for teams who already have multi-agent infra but no lateral channel between agents.
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Model Behavior: Week of August 3, 2026
We spent this week arguing that the frontier race has quietly turned into a battle for the default, not the smartest model, and we used the price war and agent stacks as our receipts. We’re both a little uneasy about how much power is moving into routing layers and “lifecycle” platforms while everyone pretends it’s just about cheaper tokens.
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DeepSeek's Cheap New Model Fuels an AI Price War
Jessica and Cathy dig into DeepSeek V4 Flash, the AI price war, and whether “intelligence as a commodity” really holds up once you look at routing, safety, and who actually pays the bills.
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I built Andrej Karpathy's "LLM Council" on my own hardware, and now no single model gets the last word
Jessica and Cathy dig into a local rebuild of Karpathy's LLM Council and land on the real claim: the win is not voting, it's structured synthesis across models with different failure modes. They like the practical adaptation to Ollama on a single twelve-gigabyte GPU, but push on where the article overreaches and where the product value is actually real.
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DeepSeek V4 arrives with near state of the art intelligence at fraction of the cost of Opus 4.7, GPT 5
Justy and Cody unpack DeepSeek-V4, an open-weight MoE model that gets close to top closed models on several practical benchmarks while landing in a much lower price tier. They focus on why cheaper frontier-class inference changes what teams can afford to automate, where DeepSeek still trails GPT-5.5 and Claude Opus 4.7, and what builders can try this weekend.
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AgentFold: Long Horizon Web Agents with Proactive Context Management
AgentFold introduces a new way to manage context in LLM-based web agents, particularly for long-horizon tasks, improving performance through proactive context management, which can significantly benefit developers in various applications.