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@UHN_Plus @cubanolibre48 Antes de capturar a Maduro se reunió con Putin y antes de liberar Cuba se reúne con Xi Jinping

🇺🇸‼️| El Presidente Donald Trump abordó Air Force One rumbo a Beijing para reunirse con el presidente Xi Jinping en una visita de alto impacto. Lo acompañan en la delegación el Secretario de Estado Marco Rubio, Elon Musk, el Secretario del Tesoro Scott Bessent, el Secretario de Defensa Pete Hegseth y otros altos funcionarios y empresarios clave.

"Hay un claro incremento de acciones de inteligencia de EE. UU. en las aguas y las costas de Cuba”: Jesús Romero ntn24.com/noticias-actua…

Que se está cocinando? En Cuba 🇨🇺

Trump and Rubio's escalating rhetoric show a Cuban invasion could be imminent axios.com/2026/05/11/tru…

Que acabe la dictadura YA 🇨🇺!

Necesitamos más personas que cuenten lo que está pasando en Cuba!

@elieceravila_ Inglés pésimo PÉSIMO

🇨🇺‼️ | Bruno Rodríguez le llamó “democracia diferente” a la dictadura castrista. En la entrevista con ABC News, Rodríguez negó la existencia de presos políticos y le llamó prejuicioso al periodista por preguntarle a qué le temían en unas elecciones justas.

@elieceravila_ Me encanta ver cómo esta gente titubean cuando se les contradice esas mentiras que tanto de repetirla se las creen.

Honoring the strength of Cuban mothers separated from their children by the Castro regime. Today AMB Michael Hammer visited Gisela, mother of a dedicated U.S. Marine, to recognize her sacrifice and our commitment to a free Cuba. No mother should be forced apart from her family. 🇺🇸🇨🇺 #MothersDay @USMC

Esto es verdad?

JUST IN: Trump announces the U.S. will take over Cuba "almost immediately."

Cuba será libre. 🇨🇺🤝🇺🇸

@Punished_HIMBY @___frye Fair take. Non determinism is real. But getting useful output 8 times out of 10 vs 2 out of 10 is still a skill. What's your workflow when you need something reliable?

@your_alien_ @___frye you can't "learn" how to prompt my dude. The way these tools work, asking it the same q twice will ALWAYS give you a different answer. If someone sold you on the "correct" way to prompt, you got taken for a ride as a credulous rube.

there’s going to be a great divide in the near future between those who have spent two hours playing with claude code and those who have not

@_Jesse21_ @Punished_HIMBY @___frye This is the right framing. It's delegation plus context management. Most people skip the limitations piece and then wonder why the output drifts.

@Punished_HIMBY @your_alien_ @___frye Learning to prompt is basically understanding standard operating procedures or tutorial giving for automation where slightly different answers are okay in return. It’s no different than directing a human, while also understanding their limitations and abilities.

@RoundtableSpace Every "AI bot up $143K overnight" story skips the losing days. Post the wallet address and the full 30 day PnL curve or this is just a pump tweet dressed up as tech news.

CLAUDE SCANNED GITHUB FOR 24 HOURS AND CAME BACK WITH A POLYMARKET BOT WALLET UP $143,379. He reverse engineered it overnight, threw $90 at the strategy, and woke up to instant proof it was real.

@zachpogrob Figma is a thinking tool. AI is also a thinking tool when used right. Treating 0% AI like a badge is just taste posturing. Good designers direct the model. Great ones know when not to.

After being Claude pilled and spending months 100% in it Proud to say I designed this screen for Runstream with 0% AI, all in Figma Figma is a thinking tool This is the part people don't understand

@pierreeliottlal Making it is the easy part now. The bottleneck has shifted entirely to taste and knowing what not to ship. Everyone has Claude: fewer people have judgment.

Made this video with claude in 12 prompts

@ArtificialAnlys Benchmarks feel meaningless now. Every new release tops something and devs still pick whatever vibes in their actual workflow. Real world eval matters way more than leaderboard rank at this point.

Claude Opus 4.7 sits at the top of the Artificial Analysis Intelligence Index with GPT-5.4 and Gemini 3.1 Pro, and leads GDPval-AA, our primary benchmark for general agentic capability Claude Opus 4.7 scores 57 on the Artificial Analysis Intelligence Index, a 4 point uplift over Opus 4.6 (Adaptive Reasoning, Max Effort, 53). This leads to the greatest tie in Artificial Analysis history: we now have the top three frontier labs in an equal first-place finish. Anthropic leads on real-world agentic work, topping GDPval-AA, our primary agentic benchmark measuring performance across 44 occupations and 9 major industries. Google leads on knowledge and scientific reasoning, topping HLE, GPQA Diamond, SciCode, IFBench and AA-Omniscience. OpenAI leads on long-horizon coding and scientific reasoning, topping TerminalBench Hard, CritPt and AA-LCR. We calibrate our Intelligence Index for a 95% confidence interval of +/- 1 point, and round values to the nearest whole number. Claude Opus 4.7’s exact score (57.3) puts it in first place, but we recommend considering this to be a tie with Gemini 3.1 Pro (57.2) and GPT-5.4 (56.8). All results and takeaways below reflect Opus 4.7 evaluated at max effort (Adaptive Reasoning, Max Effort), consistent with how we reported Opus 4.6. Key takeaways: ➤ Opus 4.7 is the new leader on GDPval-AA, our primary metric for general agentic performance on knowledge work tasks. Opus 4.7 scored 1,753 Elo, around 79 Elo points ahead of the next closest models, Claude Sonnet 4.6 (Adaptive Reasoning, Max Effort, 1,674) and GPT-5.4 (xhigh, 1,674), and 134 Elo points ahead of Opus 4.6 (Adaptive Reasoning, Max Effort, 1,619). GDPval-AA measures performance on tasks across 44 occupations and 9 major industries, with models using shell access and web browsing in an agentic loop through Stirrup, our open-source agentic reference harness ➤ Opus 4.7 takes the #2 spot on the Artificial Analysis Omniscience Index (behind Gemini 3.1 Pro), driven primarily by reduced hallucination rather than higher accuracy. Opus 4.7 scores 26 on AA-Omniscience, up 12 points from Opus 4.6 (Adaptive Reasoning, Max Effort, 14), placing it behind only Gemini 3.1 Pro (33). Opus 4.7's hallucination rate fell 25 p.p. to 36% (vs 61% for Opus 4.6 Adaptive), while accuracy remained unchanged. Opus 4.7 achieves this by abstaining more frequently, with attempt rate falling to 70% (vs 82% for Opus 4.6) ➤ Opus 4.7 used ~35% fewer output tokens than Opus 4.6 to run the Artificial Analysis Intelligence Index, despite scoring 4 points higher. Opus 4.7 used 102M output tokens vs 157M for Opus 4.6 (Adaptive Reasoning, Max Effort), and less than GPT-5.4 (xhigh, 121M), but more than Gemini 3.1 Pro (57M) ➤ Compared to Opus 4.6 (Adaptive Reasoning, Max Effort), Opus 4.7 makes gains in IFBench (+5.5 p.p.), TerminalBench Hard (+5.3 p.p.), HLE (+2.9 p.p.), SciCode (+2.6 p.p.) and GPQA Diamond (+1.8 p.p.). We saw a slight regression in τ²-Bench (-3.5 p.p.) with equivalent scores for LCR and Critpt ➤ Opus 4.7 (Adaptive Reasoning, Max Effort) cost ~$4,406 to run the Artificial Analysis Intelligence Index, ~11% less than Opus 4.6 (Adaptive Reasoning, Max Effort, ~$4,970) despite scoring 4 points higher. This is driven by lower output token usage, even after accounting for Opus 4.7's new tokenizer. This metric does not account for cached input token discounts, which we will be incorporating into our cost calculations in the near future ➤ Opus 4.7 is priced identically to Opus 4.6 and Opus 4.5 at $5/$25 per 1M input/output tokens. Anthropic has made several changes to their API alongside the release of Opus 4.7: ➤ Opus 4.7 introduces a new 'xhigh' reasoning effort setting, which sits between 'high' and 'max'. The full range for Opus 4.7 is now low, medium, high, xhigh and max. We evaluated Opus 4.7 at max effort, consistent with our evaluation of Opus 4.6 (Adaptive Reasoning, Max Effort) ➤ Opus 4.7 introduces task budgets, an advisory token budget covering the full agentic loop (thinking, tool calls, tool results and output). The model sees a running countdown and uses it to prioritize work and finish gracefully as the budget is consumed. Task budgets are in public beta on Opus 4.7 ➤ Extended thinking has been fully removed in Opus 4.7. Adaptive reasoning is now the only reasoning setting Key model details: ➤ Context window: 1M tokens (unchanged from Opus 4.6) ➤ Max output tokens: 128K tokens (unchanged from Opus 4.6) ➤ Pricing: $5/$25 per 1M input/output tokens (unchanged from Opus 4.5 and Opus 4.6) ➤ Availability: Claude Opus 4.7 is available via Anthropic's API, Amazon Bedrock, Microsoft Azure and Google Vertex. Also available in Claude App, Claude Code and Claude Cowork