GM’s electric future depends on a new battery — and this facility
GM wants to slash EV prices by deploying new battery tech up to a year earlier than planned. This building is key to making that happen.
GM wants to slash EV prices by deploying new battery tech up to a year earlier than planned. This building is key to making that happen.
Is this significant news? submitted by /u/sstiel [link] [留言]
This is a submission for the GitHub Finish-Up-A-Thon Challenge Note: AI is currently a Hot Topic in...
Back in the 1980s a debate raged about whether it was okay to let children use calculators in elementary school. Critics warned that giving kids calculators would lead to the "destruction of student math skills." A similar debate is happening today across a range of areas, including coding, writing and even music. Will using AI lead a brain drain across these and many other areas? One of my favorite authors is Isaac Asimov. He's better known for his Foundation and Robot series of books where he contemplates whether an algorithm can successfully predict (and guide) humankind's development and the relationship between super artificial intelligence and humans. In some ways he predicted what we're experiencing today with AI: the rise of powerful, inscrutable artificial machines that are so complex humans can't understand or maintain them. In the short story, "The Last Question" he wrote: "Multivac was self-adjusting and self-correcting. It had to be, for nothing human could adjust and correct it quickly enough or even adequately enough." We're living an age that was once the stuff of science fiction. The question is: what comes next? submitted by /u/SpiritRealistic8174 [link] [留言]
Lectric, which says the U.S. market is ripe for competition and choice, has launched three new brands in the past six months.
I’ve spent the last seven months building a tool I wish I’d had in my previous roles. MimicScribe is a macOS menu bar app that fits the "AI notetaker" category. It has accurate on-device speaker identification (a first possibly?), real-time meeting talking points for discovery calls, and a fully keyboard- and voice-driven interface. I believe the accuracy of the speaker ID system is its biggest strength. I used fluid audio’s port of ( https://github.com/fluidInference/FluidAudio ) Pyannote's com
submitted by /u/SpeedAssassin [link] [留言]
While the AI fundraising machine keeps breaking its own records, some founders are building in the other direction. Mirror founder Brynn Putnam just raised money for Board, a startup focused on bringing people together through in-person games and social experiences. Cyberdeck creators are going viral crafting whimsical DIY computers that literally encourage users to touch grass. Unlike the AI-free browser crowd, this doesn’t just feel like backlash, […]
Nicolas Cage was born to play 1930s PI Ben Reilly/The Spider: part Bogart, part Bugs Bunny, 100% Cage-y.
Whether you’re considering starting a Sonos speaker setup, or adding to an existing group, the Sonos Era 100 is worth picking up. The compact, capable smart speaker is currently marked down to $189 ($30 off) at a variety of retailers, including Amazon, Best Buy, and directly from Sonos. If you want an even lower price, […]
https://gds.blog.gov.uk/2026/06/02/building-for-the-future-m... https://www.adyen.com/press-and-media/adyen-payments-gov-uk
been building AI agents for a while and noticing a pattern: the LLM reasoning part works. the part that breaks is everything around accounts, logins, and verification. agent gets to "sign up for this service" and then: - email verification loop breaks - OTP times out while the agent is mid-step - captcha or bot detection fires - session expires between steps the model figured out what to do. the infrastructure around it didn't cooperate. curious if this matches what others are building. where do your agents actually fail in production? is it the reasoning, or is it the plumbing? submitted by /u/kumard3 [link] [留言]