A I C o n t e n t C r e a t o r
Joined December 2024
- Tweets21.6K
- Following65
- Followers8K
- Likes12.2K
Breakdowns by speaker age and gender on an ASR board. Haven't seen that often. Great work @voicearena_ai
Drop 3/15: Introducing the Speech Recognition Benchmark on @voicearena_ai.
One benchmark for every use case of speech recognition, in every language. Tested on real conversations.
Dataset 1 is live: the Monsoon Conversational ASR Test Set, two-person conversations in 5 languages.
Leaderboard and public test sets at Voice Arena.
Breakdowns by speaker age and gender on an ASR board. Haven't seen that often. Great work @voicearena_ai
This quoted post is unavailable.
Jackson retweeted
What if your devices, apps and agents knew what you wanted?
You finish breakfast, and your Uber is booked.
Running late, your agent sends a “Running late” text.
You reach home, and your lights turn on.
AI is proactive now. But it still needs your yes. It waits, for you to unlock your phone, open an app and tap approve. Every time, hundreds of times a day.
AI needs its own interface.
Aina is a ring with a screen that predicts and shows you the three things you’ll need next. One flick of your thumb, and it’s done. For everything.
✦ Cues: proactive suggestions, ready before you need them
✦ Voice: talk to your agents, take notes, dictate
✦ Remote: control your music, Mac and TV
✦ Calls: right from your hand
Pre-orders open now
aina.com
the thing with aether is the agent's machine doesn't care what your laptop is doing. lid closed, wifi gone, the task keeps running and the terminal is still there when you're back.
Today we’re introducing Aether @aetherruntime.
The fastest cloud coding agents in the world that you can use with your existing subscription
Give it a task and just 20 seconds later your build is running on its own cloud machine. You can pick up from your phone, watch every line, and step in whenever you want as if it was local. Close the laptop. It keeps going.
It runs Claude Code or Codex on the Claude or ChatGPT plan you already pay for so there’s not a 2nd AI bill. You only pay for the machine.
When it’s done, if code review is enabled, a reviewer agent runs the code with the changes, which catches classes of bugs that can't be found from static analysis.
Before building Aether I built infra at Apple, Uber, and HeyGen. I built Aether because the cloud agents I tried before all had drawbacks, and I couldn't imagine building something without it now.
It’s free to start. runaether.dev
Jackson retweeted
Our OSS skills just got a huge refresh
update HyperFrames skills to unlock /reverse-any-video and the top generative models with Pro
sign in and get access to 10,000+ music tracks, sound effects, 75,000+ stock images and tts for free
npx hyperframes skills update
Jackson retweeted
Most think vibecoding at scale is slop. Here’s a counterexample.
Today we release a 16M-line formalization of the entire Stacks Project, critical infra underlying modern math, with optimized code quality and its highly interconnected structure preserved.
A mathematical city 🌆
Not spending the whole balance is a perfectly valid choice. @vosu_ai lets you make it without a monthly reset.
VOSU just killed AI subscriptions.
You get the same AI models. Up to 70% cheaper than major competitors.
No subscriptions.
No monthly credit resets.
No expiring credits.
Start with just $1.
Stop wasting your hard-earned money on platforms that take away credits YOU paid for.
Busy month? Life happened? Your credits are still YOURS - @vosu_ai has your back.
You paid for them. Why the hell should a calendar take them away?
Your creativity doesn’t run on a billing cycle.
Jackson retweeted
We just raised $120M, with a $1B valuation, to build software that keeps itself running.
AI is writing more code than ever. It’s also making production less reliable: more code, shipped faster, understood by few.
@traversal_ai understands how production systems fit together, finds the root cause of incidents, and helps prevent the next one.
Engineers at Nubank, Harvey, PepsiCo, DigitalOcean, and a growing list of Fortune 100 companies use Traversal every day.
Here’s production without the drama 👇
Jackson retweeted
Introducing Archon, a video foundation model that zero-shots raw footage into finished edit in minutes.
Built by Steve Aoki and industry experts for the next generation of content.
Archon powers personal AI video editors that learn each creator’s taste from:
- Decisions made in our multiplayer editor
- Their past video catalogue
- Reference videos they cite
Every video edited makes the editor more accurate for that creator or team.
Comment "SELENDIS" for early access + 3 months free.
selendis.com
Jackson retweeted
she left @harvard surgery to build AI. she was told silicon valley would never accept her, that she would die under a bridge.
so she cold-messaged @KiteVC on linkedin because he backed canva early. he replied the next day and sent her to @SanghaCapital. one 90-minute call later, they were her first investors.
@larsras, co-founder of google maps, came in next. @amandaterry of @ACTAIVentures backed her at pre-seed. then @M13Company and @latifperacha led a $5M seed, with xAI co-founder @ChrSzegedy.
@heyrobynai just launched and ran out of invites on day one.
now her dad thinks they'll IPO in three years.
@iamjennyshao on nontechnical, episode 5.
00:00 she left her harvard surgical residency for a startup
00:46 "leave what? leave surgery? leave harvard?"
01:14 "you're gonna die under a bridge"
03:18 how do you walk away from yourself
05:03 now her dad thinks they'll IPO in three years
06:10 why melanie perkins and canva
07:02 the cold linkedin message to bill tai
07:49 one 90-minute call, then the round
08:32 why people are scared of AI
13:13 "decide who owns the complexity"
16:19 everyone gets their own jarvis
17:37 what if AI takes every job?
19:06 robyn, as in robin to your batman
19:52 "help my dog live longer"
28:45 "as a founder, no one's dying"
30:37 530 builds in one year
32:37 three kinds of surgeons
36:52 why AI forgets everything about you
37:30 three years with nobel laureate eric kandel
40:45 "it's like 50 first dates"
44:11 can AI just order my pizza?
45:19 would you give AI your credit card?
47:59 "jenny, I just need more tokens"
49:50 brian chesky lived with his users. she texts hers.
What would convince us that preference testing needs updating? Ties alone aren't enough. Changes in sensitivity, reproducibility, and relevance would be worth examining.
Drop 2/15
Are we actually measuring the things we ultimately want our voice AI models to achieve?
The best AI voices are becoming hard to tell apart.
From each other. Not from humans.
🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech.
We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time.
With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI.
If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal?
We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system.
Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure.
Results are now live on @voicearena_ai.
Jackson retweeted
We’ve raised $1.3M from YC & Afore Capital so you never have to type or speak again.
Typing is slow. Talking into your computer is awkward. Subvocal fixes both
Our glasses give you the speed of speech without you making a sound or touching a keyboard.
It tracks your internal speech muscles with non-contact sensing and decodes silent, almost invisible mouthing into text at more than 200 words/min.
Pre-orders are now live at:
subvocal.co/preorder?utm_sou…
Jackson retweeted
Introducing Cartesia Managed Agents: our end-to-end voice agent platform for enterprise.
#1 on @ArtificialAnlys Speech Agent Arena and @ServiceNow EVA-Bench, built by co-designing our voice models and harness as one system.
Check it out → cartesia.ai/blog/managed-age…
Jackson retweeted
All that said, I'm generally excited about this new paradigm.
It gives us a whole new axis to scale AI models - towards personalized responses.
Which is more impactful to large scale adoption than just intelligence.
If AI can understand you, it can make things more beautiful for you. We are hoping to help make a more beautiful world for everyone.
Jackson retweeted
BCI is moving away from clinical applications to consumer uses, and applications like these will become more abundant w time.
Robust and dependable regulation on user safety and standards of use on neural data can do great work in setting such standards for safety that allow users to trust such systems.
If brain signals can be used to understand private thoughts and personal preferences, users will want the service providers to be more trustable, and sufficient regulation to enforce the same.
Jackson retweeted
We wanted to talk about this publicly and share how we're thinking about responsibility that comes with such capabilities.
We are focused on how to have higher standards on user consent and are investing in edge inference, and training on encrypted neural data.
We have some interesting work here that I can’t wait to talk more about.
Jackson retweeted
We wanted to be careful about this release given the societal impact of AI that can change faces.
It can cause negative impacts like amplifying body dysmorphia, and narrowing beauty standards, can allow a bad actor to actively influence audience feedback.
Jackson retweeted
Here’s how that works on altering faces based on personal preferences learnt using neural feedback.
Jackson retweeted
Unlike DPO which is generally used to tune text-to-image models, our paradigm is on-policy and doesnt require a preference dataset.
We show that even a simple embedding + k-NN based reward model works well so no explicit reward model has to be trained.
The models move personal preference more strongly than population level preference showing individual preference is captured from EEG.
We also see seed stability across runs where the model converges to similar levels across seeds.
Randomizing the rewards shows that the rewards don’t move, indicating that the reward signal does come from EEG and is not an artifact of training.
Jackson retweeted
In most aesthetic areas, personal preferences deviate quite a lot from population level preferences that internet scale AI models converge to.
This leaves people with poor satisfaction when trying to use these models for tasks that require taste.
So far, there was no way to solve this since getting reliable preference measures from every user is not possible at scale.