apimade

5 ms·

1.
by apimade 8d ago
For TTS I launched this like this week based on a Reddit thread of recommendations, added a new one to it.. I want to say on Wednesday, but this week has been a blur. Problem I’ve found with similar sites is I can’t run a lot of the models,
2.
by apimade 11d ago
Darwin TTS is based on Qwen3-TTS https://huggingface.co/zeropointnine/Darwin-TTS-1.7B-Cross-Q...
3.
by apimade 11d ago
https://apimade.com/audio-compare.html Added it to my blind TTS model comparison leaderboard. So far Darwin TTS is the open model leading the pack, ElevenLabs is at the lead.
4.
by apimade 1mo ago
512GB memory available in October. Stellar move, Apple.
5.
by apimade 1mo ago
Liquidity providers like Jane Street, Citadel, et al make money on the spread. They also buy order flows from integrators, and retail investor order flows are now a product. i.e. retail investor → brokerage platform → clearing/executio
6.
Show HN: I modded the Codex client to auto-route to the "right-sized" model(apimade.com)
2 points by apimade 1mo ago|0 comments
7.
by apimade 1mo ago
Skip signup: Cmd+Option+I > Console > 'allow pasting' const onboarding = document.querySelector('#onboarding'); const app = document.querySelector('#app'); onboarding.style.setProperty('display'
8.
by apimade 1mo ago
I guess the question is; is this the late-cycle cash-out (aka harvest pricing) akin to Sun Microsystems at the dot-com peak -- or is it a repeat of the crypto pricing hijinks we've already seen from Nvidia, where they're just expl
9.
by apimade 2mo ago
In my experience, program requirements are mostly there for the lawyers. If you act in good faith, communicate clearly, and conduct yourself reasonably, most companies will work with you — even when you've technically wandered outside
10.
by apimade 2mo ago
I've disclosed vulns across just about every industry — banking, healthcare, oil & gas, government, cybersecurity, etc -- and to some of the largest companies in the world, OpenAI, Salesforce and Google. I've been doing this f
11.
by apimade 2mo ago
They work with HFT/quant firms. Look at some of their former engineers who are now at matX. Intel/Barefoot Tofino 2, VHDL/SystemVerilog, FPGA, QSFP28 (100GbE networking), P4 programming. Their buyers don’t have customer stori
12.
by apimade 2mo ago
Oh this was on company issued devices, I don’t keep the source code! I was just explaining how this is something that probably should have triggered an investigation, but didn’t.
13.
by apimade 2mo ago
You’re so right, I totally forgot how normalised it was to take common functions and classes and factories. I guess ultimately, it was all worthless anyway thanks to LLM’s. I actually recall the lead engineers in my department coming into w
14.
by apimade 2mo ago
The only _public_ example we know. This is definitely being done with private models by HFT/quant firms, data processing agencies/orgs (large intelligence agencies, _every_ data analytics org, etc).
15.
by apimade 2mo ago
Data theft (i.e. taking corporate IP) was normalised until very recently (I'd say the last 2-3 years with the rise of the adoption of DLP and public litigation). A few examples I can think of thing I've heard _just_ in my own care
16.
by apimade 2mo ago
8800 GTX in 2006: 768 MB of GDDR3, with 86.4 GB/s of theoretical memory bandwidth. GTX 1080 in 2016: 8 GB of GDDR5X, with 320 GB/s. RTX 5090 in 2026: 32 GB of GDDR7, with 1.792 TB/s. This is fun, what's next?! PCI 8.0 is
17.
by apimade 2mo ago
8800 GTX in 2006. Cutting-edge, an insanely powered consumer card for the time. Theoretically around 0.3456 TFLOPS. 1080 GTX in 2016. Cutting-edge, an insanely powerful consumer card for the time. Theoretically around 8.87 to 8.9 TFLOPS. 50
18.
by apimade 2mo ago
Pixels can be faked. 70mm IMAX, as Nolan intended, is the ideal setup.
19.
by apimade 3mo ago
In my experience, this is the path many developers take. I’ve consulted to hundreds of companies over the years, and it’s alarming how often I’ve encountered decisions driven by what someone wanted to learn or work with, rather than what wa
20.
by apimade 3mo ago
This is what happens when you give people tools that let them achieve an outcome, without necessarily giving them the judgement or expertise to know whether the outcome is any good. If you asked me to build a house, I could probably assembl
21.
by apimade 3mo ago
Doesn’t appear to be at feature parity to GAM yet. https://github.com/GAM-team/GAM/wiki
22.
by apimade 3mo ago
Pick the longest answer, you’re right 97% of the time. This is true of any LLM-generated quiz.
23.
by apimade 4mo ago
I’m glad we could establish the ad is wearing a hat. https://youtu.be/lC5lsemxaJo
24.
by apimade 4mo ago
So, consider this a layman explanation of why this change is bad from someone who spends their time securing end-users. This change is good for the majority of users, but is actually bad for large enterprise customers and highly-regulated c
25.
by apimade 4mo ago
For tech B2B companies where the founders or executive team hold the majority stake in the organisation, yes. A failure to disclose or respond when there is a public notice on an .onion address, or a sample set of your customer data has bee
26.
by apimade 4mo ago
There's already a playlist: https://www.youtube.com/playlist?list=OLAK5uy_mUvvqf3A2l68yA...
27.
by apimade 4mo ago
It makes sense when you have a somewhat fixed core team size. Frankly, in some regards, this is the responsible thing to do. It means they’ll never grow modules or the codebase beyond what the team can reasonably maintain. However on the ot
28.
by apimade 4mo ago
What you’re concerned about doesn’t stop at the employer. Anyone with access to data being processed about you may have incentives that align similarly with your employer’s use case. Advertisers, Internet service providers, phone manufactur
29.
by apimade 4mo ago
It's moreso the "AI-isms" that irk me. It's interesting, but I'm not finishing the video because once I notice it -- I can't help but focus on it. Instead, I tl;dr'd the transcript. People question my use
30.
by apimade 4mo ago
[flagged]

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