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Most builders go from requirements straight to code. Then they spend days adjusting layouts, fixing flows, and rebuilding things that should have been caught earlier. Today we are shipping Designs in BrainGrid, a new way to visualize your app before you build it. Start with a prompt. Get a design tied to your requirement. Iterate by chatting with the agent, annotating what needs to change, or selecting individual elements for precision edits. Desktop and mobile views are there from the start. No surprises when you go to build. The gap between "what I described" and "what got built" is where time disappears. Designs closes that gap.
👀 https://t.co/NOZsB74aAu
TGIF https://t.co/Mc9Ge2Zn0e
Introducing Skills for Perplexity Computer. Reusable capabilities and actions that Computer applies automatically when needed. Teach it once, and Computer remembers forever. Create your own skills for any tasks you perform repeatedly. https://t.co/zcc0QK4bQs
No more manually pulling data. We gave Perplexity Computer a simple prompt and a free Federal Reserve API key. Minutes later: a fully formatted Excel spreadsheet with live macro indicators and charts. https://t.co/HXLI3LptUy
This @perplexity_ai usecase blew my mind. I've always wanted a tool that tracks all S&P500 earnings and key things said by executives in their earnings calls. I simply do not have the time and bandwidth to read all 500. Prompt: I want an interactive dashboard that tracks every single earnings report in the transcripts of the S&P 500 companies every quarter. Note common themes that executives are talking about. Keywords and trends that could help me potentially make money and identify larger trends. As a momentum trader. S&P 500 Earnings Intelligence Dashboard is live and fully updated with 484 company transcripts covering the latest earnings season. What's inside: 5 KPIs at a glance — total companies, themes tracked, momentum signals, average sentiment, and sector coverage Theme frequency chart : aggregated by GICS sector, so you can see which sectors are driving each narrative (AI CapEx, margin expansion, regulatory risk, etc.) Sector sentiment ranked as horizontal bars — Utilities leading at 0.79, Consumer Staples trailing at 0.66 12 momentum signals — 8 bullish, 3 caution, 1 energy transition — with the tickers behind each signal Searchable executive quotes with sector filters and pagination across all 484 companies Full sector breakdown showing every company's sentiment, themes, and key quotes Recurring refresh: A quarterly refresh is scheduled for May 15, Aug 15, Nov 15, and Feb 15 at 9am EST (cron a07f9c7c). Each run will pull fresh transcripts for all S&P 500 constituents, reprocess through NLP, and redeploy the dashboard automatically. @jeffgrimes9 @dnlkwk @alexhong @AravSrinivas Computer IS INSANE. Can't wait to see what else I can build for myself.
Monitoring the Situation: World Radio. Built with Perplexity Computer. https://t.co/bgPVnFKNUi
Prad: "Oh that's a cool view, let me task @perplexity_ai Computer to create this with live data and an interactive dashboard" Result: https://t.co/yqpXdWE7qe
https://t.co/DZkAx8pmul https://t.co/Azj1Ct8Ff2
Skills are among the most consequential new tools for AI, and Anthropic just released a very impressive nontechnical Cowork Skill that builds Skills, including doing interviews & providing benchmarks. I think you still need to add the human touch, but this is a big leap forward https://t.co/r4fCV9roWp
On most games, performance is flat or even decreasing. What went wrong? Using classic NLP, we find AI models suffer from low discourse coherence, leading to weak performance despite relatively high information density - even when using twice as many tokens as humans. https://t.co/piUFPWyLnO
My Excel toolbar right now. They are all different from each other in ways that are only clear when you use them a lot, and which also differ from the results if you ask Claude or ChatGPT on their websites to create an Excel sheet, or if you use Cowork or Codex. Complicated! https://t.co/iAo1cxZPXg
Another unsolved (& admittedly hard) AI benchmark: "write a satisfying 10 paragraph murder mystery. the pieces you need to solve the mystery should be clear enough in the first five paragraphs that you could solve it, but obscure enough that the vast majority of people will not" Errors are revealing: -Claude forgets to add the actual clue to the puzzle (and the details are too obscure), a classic planning problem for LLMs, and no, using Cowork or Code doesn't help. -ChatGPT 5.4 Pro creates a completely obvious clue and then proceeds to write with the over-elaborate metaphors and complications that have haunted ChatGPT fiction. Pro did better than Thinking, though. -Gemini 3.1 Pro is closest, but the ice is a little obvious, and it completely flubs the explanation about why the ice thing was important.
Some people casting doubt on this report, so I am deleting. But the main point remains! https://t.co/AHr3H0fxTV
I have always wondered about the answer to this question, so answering it would be really good for engagement: A young boy who has been in a car accident is rushed to the emergency room. Upon seeing him, the surgeon says, "I can operate on this boy!" How is this possible? https://t.co/HZZzdIHfW2
Amazing to see the two worst forms of AI posting in a QT. The original post misinterprets a highly-discussed paper from 2025 and calls it breaking news. Than that is retweeted by someone else giving even more wrong info (from model performance to benchmark names). 1M views. Bleh https://t.co/bRVGYSGG9m
Anyhow, the original paper is quite interesting, and, yes, models have continued to improve at SimpleBench, the hallucination test. https://t.co/IWPjxWmQz5
I just discovered LinkedIn has short-form video and the half of the videos are just Shark Tank clips. https://t.co/T49daSJR8o
Humans communicate through language and interact with the world through vision, yet most multimodal models are language-first. What happens when we go beyond language? 🤔 Beyond Language Modeling: a deep dive into the design space of truly native multimodal models Paper: https://t.co/KOpmL1PItn Project: https://t.co/Oy6XuEtUAi
Humans communicate through language and interact with the world through vision, yet most multimodal models are language-first. What happens when we go beyond language? 🤔 Beyond Language Modeling: a deep dive into the design space of truly native multimodal models Paper: https://t.co/KOpmL1PItn Project: https://t.co/Oy6XuEtUAi
Not only is Russia not winning, Ukraine would be decisively winning, but for Trump and his negotiators propping up Putin. We have taken sides, and we have taken the wrong side. If that is because of personal side deals with Russia, it’s unforgivable. https://t.co/a4CZo9KRqq
https://t.co/3zK7KT07I5
https://t.co/3zK7KT07I5
Beyond Language Modeling An Exploration of Multimodal Pretraining paper: https://t.co/GmtPAQDo8T
