Ugh, yeah I really don't like mocking culture – I use mocks exclusively for external services that I have no control over, eg I'll mock an HTTP request against an external API so my test suite works even if that API is rate-limited or flaky
INNOVATION
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Integration Tests and Code Maintenance: A Modern Perspective
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I've always been much more interested in integration tests than lower level tests myself, but that's because when maintaining tests is expensive it's important to have the highest value, most refactor-supporting tests possible Maintaining tests is much cheaper now
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ARC Prize Sets Actionable Goals for AGI Research Progress
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ARC Prize's mission is to provide actionable goals for AGI research and to measure progress towards them.
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AI Agents Writing Tests: Cost-Benefit of Code Generation
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That's mostly true, but I'm not convinced it's harmful to have agents also write tests for lower level details – code is cheap now, and I don't mind agents throwing away dozens of existing tests when they change how a feature works
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ARC-AGI-3 Benchmark Results and Saturation Timeline
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ARC-AGI-3 benchmark is here It took from $2 to $9k for frontier models to complete the task at 0.2-0.3% acheivemnt. How soon would you expect it to get saturated?
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Fireworks API Reliability and Model Latency Status Concerns
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Fireworks is super cool – but it was a bit flaky yesterday. Are you guys overloaded atm? Your status shows all-green; does it fully check model latency as part of its status checks?
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Robot Bipédal Dual-Arm pour Opérations Logistiques Haute Charge
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Dual-Arm Bipedal #Robot Designed for High-Payload Logistics Operations
— Ronald van Loon (@Ronald_vanLoon) 25 mars 2026
by @tweetciiiim
#EmergingTech #Technology #Innovation #Tech pic.twitter.com/B2oykv52XFDual-Arm Bipedal #Robot Designed for High-Payload Logistics Operations
by @tweetciiiim #EmergingTech #Technology #Innovation #Tech -
AGI Autonomy: Self-Adaptation for New Tasks
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Yes, if it's AGI it should be able to "make its own harness" for a new task, or just internalize it.
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Jensen Huang Discusses Open Frontier Models with AI Leaders
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Different voices. Same answer: open models.
— NVIDIA (@nvidia) 25 mars 2026
NVIDIA Founder and CEO Jensen Huang sat down with the leaders from @mistralai, @bfl_ml, @cursor_ai, @LangChain, @perplexity_ai, @reflection_ai, @thinkymachines, @allen_ai, @evidenceopen, and AMP PBC to discuss the rapid rise of open… pic.twitter.com/wha1gE3W5oDifferent voices. Same answer: open models. NVIDIA Founder and CEO Jensen Huang sat down with the leaders from @mistralai, @bfl_ml, @cursor_ai, @LangChain, @perplexity_ai, @reflection_ai, @thinkymachines, @allen_ai, @evidenceopen, and AMP PBC to discuss the rapid rise of open frontier models. Get the top takeaways from the frontier of AI: nvda.ws/4uR6eEV
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AI Model Development Pace Challenges Environment Creation Timeline
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This would have been materially impossible to do even if we wanted to, since it took us an entire year to create the environments, while new AI models come out every month. By the time the latest SotA model is out, the full set of environments already is already shipped.