OpenAI and Broadcom announce chip designed for LLM inference at scale
The silicon race is heating up amid the struggle to keep up with demand.
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The silicon race is heating up amid the struggle to keep up with demand.
Revenue quadrupled to $41.45 billion compared with the same period a year ago. The company's profit, meanwhile, rose from $1.88 billion to an incredible $28.2 billion year-over-year.
We still don't know why RFK Jr. overruled CDC expert to order strict quarantines.
If you're building AI agents that work with browser screenshots, you already know the pain. You take a full 1920×1080 screenshot, pass it to GPT-4o or Claude, and watch your token bill climb — while the model downscales the image anyway and blurs the exact text you needed it to read. There's a better way. The problem Vision LLMs are expensive for two reasons when you feed them full screenshots: Token cost — a full screenshot can cost 10–20x more tokens than a small crop Accuracy loss — models internally downscale large images, blurring fine text, labels, and UI elements But your agent already knows where to look. Browser automation tools like Playwright and Puppeteer give you getBoundingClientRect() — the exact pixel coordinates of any element on screen. So why are you sending the whole screenshot? The solution I built a stateless pay-per-use API that takes a screenshot and pixel coordinates, and returns just the cropped element as a lossless PNG — ready to pass directly to your vision LLM. POST /crop { "image" : "<base64 screenshot>" , "x" : 120 , "y" : 45 , "width" : 640 , "height" : 80 } Returns: { "success" : true , "data" : { "base64" : "iVBORw0KGgo..." , "mime" : "image/png" , "width" : 640 , "height" : 80 , "bytes" : 4821 } } A 4KB crop instead of a 2MB screenshot. Same information. 95% fewer tokens. How payment works Here's where it gets interesting. The API uses the x402 payment protocol — HTTP's long-dormant 402 Payment Required status code, finally put to use. There are no API keys. No accounts. No subscriptions. The agent pays $0.0005 USDC per crop on Base L2 automatically. The flow: 1. Agent POSTs to /crop (no payment header) ← 402 with payment instructions in headers 2. Agent transfers 0.0005 USDC to recipient wallet on Base (near-zero gas, ~2 second settlement) 3. Agent POSTs again with x-payment-tx-hash header ← 200 with cropped PNG The entire exchange happens inside the HTTP request cycle. No human intervention. No billing dashboard. The money lands
The Internet of Things is now a phrase you see on product boxes, in boardroom slide decks, and across thesis titles in engineering departments everywhere. But it has a surprisingly precise origin. The term was coined in 1999 by a British technologist named Kevin Ashton, and it was not born in a research lab or an academic paper. It started its life as the title of a corporate sales presentation. A slide deck, not a laboratory In the late 1990s Ashton was a brand manager at Procter & Gamble, the consumer goods giant behind products you would find on any supermarket shelf. He was wrestling with a mundane but expensive problem: store shelves kept running out of a particular shade of lipstick, even though the warehouse had plenty in stock. The supply chain simply had no reliable way to know, in real time, what was where. Ashton's proposed fix was radio-frequency identification, or RFID: tiny tags that could be attached to products and read automatically by sensors, with no human scanning each item by hand. The vision was that physical objects could report their own location and status, feeding that data up into computer systems without anyone typing it in. To sell this idea to executives, he needed a title that would make supply-chain tagging sound as exciting as the technology dominating headlines at the time. So he linked his RFID proposal to the hottest topic of 1999 and called the presentation "Internet of Things." By his own account, years later in RFID Journal, the choice was deliberate. Tying tags and sensors to the red-hot word "internet" was the surest way to get senior people in the room to pay attention. The pitch worked well enough that the phrase stuck, and Ashton went on to help found the Auto-ID Center at MIT, a research group that did much of the early standards work that made networked RFID practical. Why the name was actually a good description It would be easy to dismiss the term as a marketing flourish, but it captured something real. Ashton's point