Rishi Dean

@Shpigford I just went through this. Export to Obsidian and then use Claude Cowork to ask questions of the entire corpus or specific notebooks.

evernote is doubling the price of my subscription to an arguably insane price, even for a PE-acquired business. we've got 15+ years of docs stored there (huge % are scanned PDFs). trying to figure out my move here. i don't want another note taking app. i kind of just want a vault for dumping all our random document files (again, mostly PDFs) that's thoroughly indexed/searchable. big caveat: needs to be also be easily shared with my wife. wonder if there's something there from a biz perspective? 🤔

@BillSimmons Whomever is in charge of the NBA Playoff tv schedule is an NFL plant

Cannot for the life of me figure out why… 1. The NBA moved the lottery to a Sunday afternoon 2. They put it at 3 ET before the 2 playoff games on Mother’s Day no less. It’s almost like they’re trying to sneak it by us. Conspiracy Bill is on alert!!!!!!!!

@realmadhuguru @Google Awesome run Madhu!! You really changed the game there! Enjoy some downtime, and when you’re ready to tackle the next thing….call me!!

I'm moving on from @Google. I had the privilege of helping build two businesses from zero: first across Search & Ads, then Gemini. Three years ago, OpenAI and Anthropic were in the lead. We built what it took to compete: the playbook for building AI models, the customer feedback flywheel, and the enterprise business. Gemini 3 was the moment those systems came together. To the Gemini team: we went from underdogs to competing at the frontier. Keep pushing. For now, I'm enjoying the emergent capabilities of some real intelligence at home - my toddler. She's been quietly shipping.

@MrPassive_ And the Spring concert is at 1PM on Wednesday

The parenting books don’t do enough to warn you about the fact that work ends at 5:00, the school gets out at 2, and soccer starts at 3:30.

@petergyang Totally get this for “productivity” but chat is a great thought partner to riff with when exploring ideas, also use for deeper answers to questions, etc. To me they’re apples and oranges.

People asked similar questions in the mid-90s like. Why would anyone want to watch TV or Radio on the internet? We’ve solved media but 30 years later still haven’t brought money natively online.

Tell me how much you’re personally spending on tokens (non work/biz), and I’ll tell you how much I trust your opinions.

@dadiomov Micro transactions, cross border, underbanked, no fees, programmable money.

I don't understand the premise that "agents must use stablecoins." Why can't an agent remember the 16 digits of a credit card? Sorry maybe I'm a payments n00b. Stablecoins have a lot of great use cases, but ecommerce shopping is pretty well optimized already for cards.

He enjoyed this season the most. Anyone ever consider in '24 how much pressure they were under?? Outcome was great, but process was challenging. Meanwhile in '26, no one expected anything so he could just play w/o pressure. Which one seems more fun? Wouldn’t you consider this season a success? But just breathing that has everyone trying exile him to Milwaukee??

Jaylen brown doubles down that this was his favorite season in the NBA and he doesn’t view it as a failure, despite the result. Adds that he got to see Jayson Tatum persevere through adversity.

He enjoyed this season the most. Anyone ever consider in '24 how much pressure they were under?? Outcome was great, but process was challenging. Meanwhile in '26, no one expected anything so he could just go out there and play w/o pressure. Everyone admits he made a leap too. Which one seems more fun? And why is saying that worth being exiled to Milwaukee??

This whole Jaylen Brown situation feels like it's going to become the story of the summer. That means it's either going to be nothing but smoke or has the potential to get messy. I've got no idea which way it will go.

@AshNicoleMoss TMac left Toronto to be “the guy”. The J’s have been to 6 ECFs and win a chip. If that was an issue it would have shown itself before year 10.

for those who want full context — this is what is being discussed:

on Jaylen Brown's reported "frustration" with the Boston Celtics: "what T-Mac is alluding to is that the return of Jayson Tatum and him (Brown) no longer being "the guy" upset Brown (...) and that's an issue with the foundation of what makes this team successful." @CBSSports

@AdamTaylorNBA No way. This is going way too far.

Celtics fans — would you?

@Defi_Warhol @stripe @circle Stripe has distribution and far better tech teams

The race between @stripe and @circle is ON. It looks like Stripe decided it was cheaper to buy the infrastructure than build it from scratch. In 18 months, they acquired or built every piece needed to move stablecoin payments end-to-end. Each of these projects covers a different layer of the payment flow: 1. @Stablecoin → stablecoin issuance and orchestration 2. @privy_io → embedded wallet infrastructure 3. @Valora → mobile wallet and Web3 infra 4. @tempo → permissioned L1 payments chain Stripe now owns every layer of the payment stack itself. It's not surprising that Circle did the same thing. They just started by issuing USDC first, then built the infrastructure around it. Let's see which one can process more payment volume.

This is what happens when you only read about it, and aren’t actually building anything.

@AndrewDBailey Because the NBA optimizes for their broadcast partners and not their fans.

Why on earth would the NBA have these games overlap?

@WorldWideWob For every Celtics hater - take your moment. We got BEAT that series. It sucks, especially after the season we had. Nothing is guaranteed in this league. Celebrate you earned it.

Celtics fans therapy session. Let it all out. This is a safe place.

@fortelabs Drafts 4

Can anyone recommend a dead simple, easy to use notetaking app based on markdown files? Obsidian is far too complicated for me. I'm looking for Apple Notes, but with markdown storage

@WatcherGuru If you can’t beat ‘em….pay $40B

JUST IN: Google $GOOGL to invest up to $40,000,000,000 in Claude AI developer Anthropic.

A pre-made wrap at SFO (out of a refrigerated case) costs $18.75 🫠

@yohaniddawela Couldn’t they just use home price as a better proxy? Data is available too.

Google trained an AI to predict your neighbourhood's income by counting the coffee shops, bus stops, and high-rises on a map. Nobody told it what income was. The model is called S2Vec, published this month by Google Research as part of their Earth AI initiative. It takes the built environment (every building, road, park, and business in an area) and converts it into a layered image. Three coffee shops and one park in a grid cell become pixel values. The AI then reads that image the same way a computer vision model reads a photograph. The training method is the part that matters. S2Vec uses masked autoencoding: you show the model a patch of a city with chunks missing, and it learns to fill in the gaps. Show it a cluster of high-rise apartments next to a subway station, mask out a section, and it predicts a grocery store belongs there. Do that millions of times across the globe and the model learns the deep spatial grammar of how cities organise themselves. No human ever labels a region as "financial district" or "suburban residential." The model figures out those groupings on its own from the geometry of what's built where. The output is an embedding, a string of numbers that acts as a mathematical fingerprint for any location on Earth. Feed those embeddings into a prediction task and S2Vec can estimate population density, median income, and carbon emissions for regions it has never seen before. On zero-shot geographic extrapolation (predicting for regions entirely absent from training data) S2Vec was typically the best-performing individual model. It matched or beat satellite imagery baselines like RS-MaMMUT and outperformed GEOCLIP on socioeconomic prediction. The best results came from combining S2Vec with satellite image embeddings. Built environment data alone couldn't capture vegetation, terrain, or transportation patterns well enough for environmental tasks like tree cover and elevation. But fused together, the two modalities outperformed everything else. The standard approach to geospatial ML has been hand-crafting indicators for every new problem. Predicting air quality meant building a bespoke feature set. Estimating housing prices meant building another one. S2Vec replaces that with a single general-purpose representation that transfers across tasks. The training data is map features, not satellite pixels. That distinction is pretty important to understand. It means: map data updates faster, costs less to process, and covers built infrastructure at a resolution satellite imagery can't always match. A satellite sees rooftops. S2Vec knows there are three cafes, a pharmacy, and a bus stop underneath them. Google's broader Earth AI pipeline now has three foundation models working in parallel. 1. PDFM for population dynamics. 2. RS-MaMMUT for satellite imagery. 3. S2Vec for the built environment. Stack them and you get a system that can read a neighbourhood the way a local understands it.