Nish Tahir
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Nish Tahir
@nishtahir.com
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Principal Engineer, ML/AI Research (Anti-hype). I can and will be wrong. My opinions are my own. Blog: https://nishtahir.com Mastodon: social.nishtahir.com/@nish
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When you dig even a little bit, there always something. $20k to have a robot do things like open doors for you. For more complex tasks a human has to remotely operate the robot.

www.engadget.com/ai/1x-neo-is...
Well-written anecdote on deep research tools for literature reviews. Manual research is still overwhelmingly best at finding relevant citations. Models are directionally helpful but often hindered by paywalls and limited webscraping capabilities.

xiangyu-yin.com/content/post...
We really missed an opportunity to make all the LLM acronyms valid roman numerals. LLM, VLLM, LVM, LMMLM...
It's worth noting that I did some googling and couldn't find anything about the architecture, models, LLM, AI stack. If the goal is transparency I'd have expected this to be publicly available to review.
Welcome new friends. 👋
I got an ad from Virgin Voyages that looked like something straight out of stable diffusion. Turns out they've been running AI generated ad campaigns. A lot of these seem very generic so I wonder how well they work for them.

adage.com/brand-market...
Inside Virgin Voyages’ agentic AI strategy that’s slashing its agency costs
The brand is using more than 50 agents to personalize marketing and help guide consumers toward booking.
adage.com
Everyone should be familiar with the DNS haiku
Don't interpret the study as Adopt AI now, there are drawbacks. It should be a guide to think about where it fits in your org
• Developer trust is the barrier to greater usage - Establish an AI usage policy, give people opportunity to experiment but don't force them to use it.
• There are mixed signals coming from other sources/survey - METR stands out and raises questions about the credibility of self reported data
TL;DR
• Mostly self reported data.
• 90% of devs use AI at work.
• Simply adopting tools fix your problems
• AI adoption is a force multiplier - if your delivery practice is good, you'll likely see some benefit. If it's bad, it'll likely make everything worse.
Speculation in AI has always been and continues to be a waste of time. Self driving was 2 years away 10 years ago. AGI was 2 years away 2 years ago and is now 10 years away.

Focus on what actually works right now and build against that. There's a lot of cool stuff already here to explore.
Alternatively get a Mac Mini or studio. Both expensive but fine options.
IMO unless you specifically care about CUDA, getting AMD's AI Max 395+ is a much better deal. The currently show better performance and you can get 2 nodes for the price of 1 DGX spark.

www.inc.com/chris-morris...
Why Your Business Should Consider Nvidia's New $4,000 Desktop Supercomputer
The DGX Spark supercomputer just went on sale. Here's what to know about the powerful machine.
www.inc.com
MCP focuses on trying to provide tools to the LLM that it can optionally use. These are more like smaller manuals the LM can reference to improve behavior on certain tasks.

You can have a skill on parsing PDFs as an example - Use pdf kit, ignore table of content, include page numbers - for example
Now that i'm looking at the numbers against the AMD AI MAX+ 395 platform, it feels like this should have been half the price.
I haven't found a compiled apples to apples against the DGX spark yet but looks to get ~49.40 tps on GPT-OSS 120b mxfp4 www.reddit.com/r/LocalLLaMA.... It's presumably a more capable platform for dev work based on review comments.
Mushoz's comment on "MINISFORUM MS-S1 Max AI PC features AMD Strix Halo, 80 Gbps USB, 10 Gb LAN, and PCie x16 - Liliputing"
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