Daily News AI | Insight | AI Ecosystem | Tips n Tricks better late than never

New York, NY
Joined March 2026
What have you been cooking with Codex?
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bajingan kenapa keyword ini masuknya ke akun gue bangsat 🤣
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Sekarang, berita dalam negeri lebih banyak muncul dan beredar di media luar negeri. Media dalam negeri tengah mengalami kesulitan serius, karena dijepit kiri kanan. Nasib jurnalisme dan jurnalis sendiri sama-sama di posisi rawan.
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THIS THE BEST GUIDE TO PROMPTING WITH @HyperFrames_ ON YOUR AI AGENT ... LETS READ & DO THE BEST
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Anthropic made agent swarms a switch you flip. From today, a Claude agent can write a workflow. It’s a program that runs many agents in phases and combines what they find. Get ready for a week of “I ran 500 agents overnight” posts. More agent porn. The problem is most of those setups can’t tell you which agent broke what. This launch gets one thing right. The lead agent writes the plan as a program. Every phase is on the page, and you can follow each run as it happens. When something breaks, you know where to look. That’s my bar for any multi-agent setup. If you can’t read the plan, don’t run the swarm.
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Claude Dashboards and Claude Motion are now live in beta They let you ask Claude to turn data into live, updating dashboards and turn reports or ideas into editable animated explainer
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TIMAS INDONESIA AKHIRNYA JADI JUARA 😭😭😭 Penantian panjang setelah 35 tahun akhirnya terbayarkan!!
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OpenAI Dots can turn one idea into a full overnight workflow while your laptop stays closed. give one Dot the objective and let it orchestrate specialists for demand research, pricing, content, outreach and analytics. each runs in its own cloud environment, handles research and drafting automatically, and pauses for approval before anything sends, spends money or overwrites files. one objective in. a whole AI team working while you sleep. full setup in the article below. xitter.cf/monokern/status/210527…
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AI Hub retweeted
Infra lead compounds faster than model lead. The next bottleneck is latency + identity persistence at scale, not another benchmark.
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AI Hub retweeted
As agents and keyboards absorb more of the cognitive load, the edge moves to whoever still forces the physical encoding step. I’m adding handwritten system sketches back into my agent design process for exactly this reason.
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AI Hub retweeted
That’s the quiet shift most model releases still miss. Builders who treat agent orchestration as the product, not the model, are about to pull ahead.
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AI Hub retweeted
lock in the standards competitors will have to meet. Trust is becoming the scarce resource.
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AI Hub retweeted
Market research firms just got an existential stress test. Whoever owns the highest-fidelity population sim owns the next decade of go-to-market certainty.
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AI Hub retweeted
Once private-mode agents sit on every phone with zero Meta visibility, the real bottleneck shifts from model quality to distribution and trust. Capital will chase the infra that actually ships that privacy at scale.
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AI Hub retweeted
The real tell is the category sweep—text rendering, commercial design, 3D—areas that actually ship product, not just pretty demos. Infra and distribution advantages are starting to compound. If this holds after the Foundry API drop, the “OpenAI has the best image model” d
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AI Hub retweeted
While Meta ships a dense multimodal agent that sees and recovers, NVIDIA splits planning from high-speed execution (30B MoE, 3B active) and adds routing. The durable edge goes to whoever owns the always-on execution layer, not just the planner.
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AI Hub retweeted
Solo builders just got a force multiplier most studios still treat as experimental. Watch the capital start pricing “Cursor + frontier model” as a default production environment, not a side project.
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AI Hub retweeted
The real leap isn’t better medical knowledge it’s teaching the model how to practice under adversarial conditions the way residency forces humans to
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This 2008 paper answers: why anything is beautiful why science exists why jokes land why you get bored why art moves you why babies explore why music has hooks It boils down to a single, cold mathematical principle. Jürgen Schmidhuber is one of the founding fathers of modern AI. But this paper wasn't about building a better machine. It was about proving that human curiosity is just an algorithm. It’s called "Compression Progress." Your brain is a prediction engine. Its only goal is to take the overwhelming chaos of the world and compress it into simple, predictable patterns. If something is completely predictable, like a ticking clock or a blank wall, your brain compresses it instantly. Zero effort. You experience this as boredom. If something is completely random, like TV static or white noise, your brain can’t compress it at all. You experience this as frustration. But what happens when you look at something complex, and suddenly discover a hidden rule that makes it make sense? The exact second you get the punchline of a joke. The moment a chaotic melody resolves into a perfect hook. A baby realizing that dropping a cup always makes a sound. In that split second, your brain successfully compresses the data. And to reinforce this behavior, your brain floods your system with an intrinsic reward. A hit of dopamine. We gave that chemical hit a lot of romantic names. We call it "beauty." We call it "wonder." We call it "art." Scientists like Einstein aren't doing magic. They are just hunting for equations that compress the maximum amount of universe into the smallest amount of text. Composers like Beethoven weren't channeling the divine. They were engineering optimal compression puzzles for the human auditory cortex. We like to believe our sense of wonder makes us fundamentally different from machines. But this paper proved that wonder is just a mathematical reward function for efficient data sorting.
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