iPhace Duo https://news.microsoft.com/surfaceduo/

The main problems from that Duo was that Microsoft didn't believe in it.

This lead them to use a garbage CPU and support it for something like 2 years.

Apple has the balls to keep updating the vision pro even after it flopped and it will probably get 7 years.

Looking back now it was quite ahead of its time.

Actually kindof awesome! ...but when I saw the phone call at the end my mind immediately went back to "Taco-Talkin' w/ the Nokia N-Gage"! => https://sidetalkin.com/original/

August 12, 2020

The fedex driver that delivers to my office is still maining one of these. Its so cool.

Zune'd

Still use mine!

I will say it was a pain in the ass to open and answer calls though when you were busy doing things.

This made history because Apple never copied Microsoft before. https://news.microsoft.com/surfaceduo/

Always loved the Surface Duo. I really liked the separation of the screens too; felt like dual monitors vs. ultrawide. It also forced the technology to focus the valueprop on multitasking versus more immersive/more bigger/more better. I'm curious about the iPhonr Duo; I have not been a huge fan of iPadOS or iOS, the former making me often wish for a macOS experience and the later having felt slower and less responsive over time (mostly due to animation speeds/aesthetic choices rather than a hardware defect).

They made a better version of a Microsoft product, this seems like par for the course.

I still enjoyed going through it, for what it is.

1. runjs promoting itself using music REPL as an example

2. author used LLM to fit a few music related ideas into the web audio API

3. they tried it with math two years ago: https://runjs.app/blog/equations-that-changed-the-world-rewr... They are clearly targeting js developers, which is one of the largest coding community

4. "The naming is not arbitrary, and the harmonic series explains why.", stop wasting tokens. Just say what it is please.

just tested it, it can be paired with a streaming setup called Voice Live. https://learn.microsoft.com/en-us/azure/ai-services/speech-s...

According to Artificial Analysis https://x.com/ArtificialAnlys/status/2095521214777442546 it is on the pareto frontier.

which raises the question, is the model in the demo actually gpt-6? or it is gpt realtime 2.1? It's unclear how gpt-6 can interact at the realtime level and if so, how can developer get access to it?

What's the point of enlarging the screen into a room? In the 1979 Put That There demo, the user at least used his hand to point things. The model is impressive but the demo felt like a step back.

Original demo (fun ending) https://www.youtube.com/watch?v=RyBEUyEtxQo

Because it looks good in a marketing video

No. You buy a minimum of $10 worth of credit, then use it at $1.49/M rate. There is no recurring charge.

There is a separate subscription based plan, which is sold out now.

Got it. But, they also charge the same for cached tokens, so that probably closes the gap on Foundation models quite a bit.

I guess Cerebras didnt intend the model for agentic coding but rather for small one shot task like title generation. At least thats why I use the free tier for.

my hunch is that their hardware can't cache

Soniox website has a live comparison demo: https://soniox.com/compare-stt

For me, Gemini-3.5-Transcribe actually has slightly lower latency. Kudos to Soniox for both paying their competitor and letting them win. But yes, Soniox is much cheaper.

Interesting, I uploaded a voice recording from a meeting I had recorded with a relatively cheap microphone.

Soniox came out really good. OpenAI started getting some things very wrong and even introduced some German. Google did okay but cut off the start by several seconds.

What's Soniox doing (left most) that's making it so good ? It was also the only one that could distinguish between the speakers.

Oh, thanks for pointing me to Soniox. It is really good. Would also pick up the words with different languages, identify and output in the right language. Looks interesting. It was much faster too, but that I cannot say much since it was on their own website.

The tokens per second speed measurement is highly inflated nowadays because most of the tokens went into thinking. I wonder if there is a more realistic measurement for "effective speed", which accounts for thinking efficiency.

Many benchmarks now measure the total cost or energy usage per completed task.