Humans inherit their agency from the self organization of cells, which inherit their agency from the self organization of particle systems in negentropy gradients. Everything leads back to the same Prime Mover
SYSTEMS
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AI API Usability and Aggregators for Agent Tooling
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J'imagine que ce sera pour les tiers plus bas. Les abonnements normaux resterons sans pub je pense
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GPT-5 unifies models, reduces switching between Codex, Operator, Memory
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GPT-5 will unify the models: OpenAI confirms GPT-5 will prioritize improving integration and reducing model switching between components like Codex, Operator, and Memory rather than introducing a new architecture. Unification of GPT and “o” models, technical hurdles led to
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Crisis-Native Intelligence Systems for Real-Time Diagnosis
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We’re not building “AI for Africa.”
We’re building crisis-native intelligence.
Systems that expect chaos and diagnose it in real time. -
AI Model Predicts Failures Through Energy Fingerprint Analysis
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But something wild happens :
The model adapts.
It predicts what fails next.
Then reconstructs missing data by cross-referencing old energy fingerprints. Not analytics.
Forensics. -
AI model architecture: agents, planning, memory, and hardware
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Ce qui me frappe, c’est qu’ils ne cherchent pas juste à faire “le plus gros modèle”. Ils construisent une vraie architecture. Chaque brique a du sens : agents, planif, mémoire, hardware… On dirait qu’ils assemblent, pièce par pièce, un vrai cerveau fonctionnel. Et
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LLMs as Causal Agents: Decision-Making and Goal Generation
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LLMs have causal power; they can be used to make decisions and control systems in the real world. LLMs can emulate agents, they can follow goals and generate goals to follow. LLMs can create a chain of thought reflect on it. LLMs generate and use abstractions. Perception is not
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Compact Language Model Architecture: 12M Parameters vs LLAMA 4
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they use word embeddings + single-layer MLPs vocab size is 18K, context window is 6 words, hidden dimension is 60, word embedding have 100 dimensions their model has approx |V|(nm + h) = 17,964 × (6 × 100 + 60) = 12 million parameters about 200K times smaller than LLAMA 4…
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Epistemological Challenges When Denying AI Capabilities
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When capability of a class of Turing complete systems is denied ("a computer/perceptron/transformer can never do X") it poses interesting epistemological and metaphysical challenges, which are unfortunately rarely discussed ("how can anything do X without breaking physics?").
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Digital Agents and Intelligent Systems Already Surround Us Daily
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Hmm disagree. Mac OS is a highly intelligent agent with lots of background tasks. Gmail is. X is. Businesses run many on your behalf, eg anytime you swipe a credit card. There’s lots of highly sophisticated, highly intelligent digital entities we use/dispatch all the time.