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@YafahEdelman A song that was solely created by less than 2000 total words of AI prompting and no additional audio recording/engineering goes #1 on the Billboard Hot 100 (the artist can upload any recordings they did for prior songs to the AI)

In celebration of passing 1k followers, I'm inviting people to reply to this asking me to forecast the probability of any AI related event happening in the future. I will provide a point estimate based largely on whatever reasoning pops into my head first.

Voice is the new computer interface. It makes technology disappear and creates magical experiences. To all my coworkers who spent years listening to me talking to my computer. This is it. It’s your turn now.

@mdotbrown Best of 5 is to the worse team’s advantage. They’ll all take that, you’re just helping them. Not against this, just noting. Apologies if you were already factoring this in

Gemini Voice really is a cut above. It’s incredible. Coming to GBrain and your OpenClaw/Hermes shortly

@BennettRayford @RealTopTenLists @simspron86522 @DKThomp Bradford & Simspron, in other sports, especially football, the seeding LEGIT matters in that if you took the same teams and scrambled the seeding, the odds of victory for each team would meaningfully change

@RealTopTenLists @simspron86522 @DKThomp It certainly does. It's clearly predictive

I think one way to get at the NBA's problem is to start w the question: What would it look like for a professional sport's regular season to be the equivalent of a pre-season exhibition period—that is, something that genuinely, truly does not matter at all? 1. For starters, seeding wouldn't matter ... bc home court advantage would barely exist, in which case the best teams could win the championship as an 8th seed just as easily as they could win as the 1st seed. 2. The playoff series would be long enough that (a) the best teams had ample opportunity to prove their superiority [unlike in March Madness, or the NFL playoffs, where 20 bad minutes can end the best team's season] and (b) you're giving casual fans a LOT of basketball to watch so they don't feel bad about skipping most of the regular season. 3. Also, you'd let the vast majority of the teams make the playoffs -- maybe by adding a "play-in" that extends potential playoff qualification to, like, 2/3rds of the league. 4. You'd have several teams that recognize (and practically celebrate!) the futility of the regular season by spending much of this period *actively and flagrantly trying to lose* bc the draft is so much more valuable than the outcome of any particular week, or month, of regular-season competition. In fact, you'd have fans actively rooting for about 1/3rd of the league to throw away most of the regular season bc they only really care about getting a high draft pick. 5. Finally, you'd have a sport where it was basically impossible to win a championship without a top 10 (or, really, top 5!?) player, in which case many franchises are rationally fixated on throwing away regular seasons to maximize their chance to draft or trade for a top 10 guy. ... okay, I think you get my point :) I love listening to basketball podcasts in the autumn and winter, and I love watching playoff basketball in the spring. But I think there are very deep structural reasons why the NBA regular season, for many casual fans, feels like a prolonged preview of an actual sport that begins in April.

@garrytan We await your arrival!

It’s official, Gemini Live 2.5 voice agent is the best It’s smart, it’s fast, it has large enough context Coming to GBrain Voice shortly

When your voice agent debugs your slides live @charlierguo is using gpt-realtime-1.5

people keep saying...

ChatGPT is now available in CarPlay. The voice mode you know, now available on-the-go. Rolling out to iPhone users running iOS 26.4+ where CarPlay is supported.

@r0ck3t23 "AI runs on voice." 💯

Olivia Moore just explained why the open office is about to die. Not because of culture shifts. Not because of remote work. Because AI runs on voice. And voice requires walls. Moore: “I do think the way that we work and when we work and how we work is going to change in the AI era.” She’s not predicting the future. She’s describing what’s already happening while most companies are still rearranging desk layouts. Moore: “Voice dictation has blown up in enterprises.” Think about what that sentence actually means. Talking to AI is faster than typing to it. Not marginally faster. Dramatically faster. Your hands were never the right interface. Your voice was. Moore: “It started with vibe coding where engineers would just talk into a mic and it would produce software for them in Cursor.” Engineers figured it out first. They stopped typing code and started speaking it into existence. Output didn’t just increase. It multiplied. The keyboard became a bottleneck overnight. Moore: “Now it’s spread to sales, marketing, and business.” This is the part that should keep every executive up at night. It’s not just developers anymore. Every department is discovering that voice is the fastest path between intent and execution. The entire workforce is about to start talking to machines all day. Moore: “That is not well suited to an open office where everyone can hear what everyone else is saying.” Here’s the collision nobody planned for. The most productive way to use AI requires talking out loud. The most common office design requires everyone to be quiet. Those two realities cannot coexist. Fifty people in one room dictating prompts simultaneously. That’s not a workspace. That’s an acoustic disaster killing the output it was designed to produce. Moore: “I think there’s going to be some cultural and even environmental changes that are going to happen to adapt to the AI world.” She’s being diplomatic. What she’s really describing is the complete physical restructuring of the workplace. Walls going up. Private rooms. Acoustic isolation becoming a competitive advantage. The open office is dead. It just doesn’t know it yet. Every company still pouring money into wide open collaborative floors is investing in architecture that actively fights the way humans will work for the next decade. The ones who figure this out first don’t get a marginal edge. They get a workforce operating at a speed their competitors physically cannot match. Not because of better models. Because of better walls.

Kelsey Plum becomes the first female pro athlete to launch a verified AI “digital twin” that fans can voice call to interact with her, per @FastCompany “It’s where we are in society… I think you’re either gonna get with it or get lost.”

@aquavoice Can't wait!

aqua voice for ios 03.01.2026

@dee_bosa Soo cool omg

ok WOW. Woke up this morning and said, for fun, lets try to recreate monday. com w Claude cowork. it wont work or anything, but we can just show our audience that its plausible. 1 hour later... I literally have my own monday. com that's plugged into my calendar & gmail and surfaced a kids bday that was not anywhere on my radar and I need to get a gift for. Can imagine next step being: order gift and have it delivered by Sunday. 2026 is WILD.

*on a first date* her: "so what do you do for fun?" me: "i have outsourced my entire life to AI agents"

@hyrumjb3 @HuggingModels We're all in this together!

@HuggingModels Open source voice models are now at the level of cutting-edge models from 5 months ago Open source always catches up fast

NVIDIA just dropped PersonaPlex-7B 🤯 A full-duplex voice model that listens and talks at the same time. No pauses. No turn-taking. Real conversation. 100% open source. Free. Voice AI just leveled up. huggingface.co/nvidia/persona…

Today, we're announcing significant new traction in our voice AI research and development partnerships. Over the past few months, we’ve quietly been expanding our focus on providing frontier voice AI training data to research labs looking to imbue emotion understanding and cutting edge expressivity into their foundation models. We believe some of the most exciting possibilities for deeper speech and emotion understanding will come to fruition this year. By training today’s frontier models to understand the nuances voice interaction—rife with subtle tones of frustration or satisfaction, “aha” moments, chuckles, sighs, backchannels, and interruptions—we believe that labs will unlock new possibilities for voice AI to become a primary interface within many applications. In our experience working with leading research labs and AI-first enterprises, a consistent pattern we’ve seen is a greater need for high-quality datasets and evaluation pipelines than for new algorithms or architectures. Researchers spend up to 80% of their time curating the data they need to diagnose model issues, fix failure modes, and improve model behavior. That’s why Hume is now focused on building the data and evaluation infrastructure needed to train next-generation voice models across industry.  With the right training, we hope that deeper voice understanding and empathy can be translated not just into more efficient interfaces but into better alignment of AI with human well-being. Read more below hume.ai/blog/data-blog…

We just crossed 200k monthly users on Tolan, a voice-first AI companion that we’ve worked closely with our friends at OpenAI to bring life to. Here’s what we learned building it: