This might be already happening. Competitor's market share (without details) is common to share. Scintilla onboarded by Walmart earlier this year might already be giving instore AI capabilities.
100 karma · joined January 13, 2017
But there is a much more stringent privacy requirement here since customers walking in those stores haven't really signed up for this analysis. Hence, difficult to just setup the camera and take continuous data for analysis.
Not an expert on this but I don't think same kind of manual effort is required anymore.
At the end of the article is this excerpt
>> Results from this research were generated using an AI computer vision model developed by the research team on Bristol’s Isambard-AI, the UK’s most powerful AI supercomputer. Isambard-AI powered the analysis of 172.6 hours of live match footage from all 104 games played between 11 June and 19 July 2026.
So, basically now merchandizers, auditors, compliance monitors, etc. have a tool using which they can quantify whether broadcaster complied with contractual requirements of showing their ads/merch/logos as per contract. And if they missed, then they can quantify the delta - to sue the broadcaster for the balance as well.
Also, it can enable many countries, where certain content is not allowed, then this tool can simply give them data points without having to employ someone, or have someone review the output of the AI tooling.
By the time your first round of beta testing is over, you may have quite a handful of such axioms and variants, which have been humanly validated!
Have you done any such experiment in this space?
Basically if a Car A is performing better (be it speed, milage or in general sense) than Car B, then it is not necessarily because its engine. It could be because of better tires, better gearbox, lighter body, better usability of features, etc.
You can implement an AI feature (like AI for BI) in different ways even with the same model - via ReAct-loop, or plan-and-execute, or hybrid. You can make it stateless, stateful, RAG-based, etc. depending upon whether you want to prioritize result accuracy or depth of analysis. You can use LLM to generate either intent (requires lesser reasoning) or the queries itself (requires much more capable model).
Your harness can adapt to the underlying model's native capabilities, or can make up for its absence, e.g. query generation in above example requires your model to have MOE capabilities but intent generation wouldn't.
I would rather wait to see how it gets adopted, if at all. Anyone aware of early reviews of the adopters of bend 2?
All that AI needs is access to all the spicy tools like nukes, unsupervised medical diagnosis/treatment, unchecked military decision making, etc. to its React loop so that humans can be completely hands-free and enjoy the fruits of AI's labor.
Maybe we need to mandate parliament (or anything equivalent in other countries) debate before giving any critical tool access to LLM? And then a UN general assembly vote to conclude the process, maybe.
Please note that I can already see that github repo has 68k+ stars. So popularity is not in question, just the viability and consistency of adoption across different scenarios.
This is the best part of this spec, but we have found from our experience that though upfront thinking changes has a lot of merits and adds clarity and alignment upfront, but it changes bit by bit in every meeting and before you know your specs are not aligned with general consensus in the team. If your team is large enough, then it gets very difficult to own the task of constructing alignment between your principal-artifacts and your evolved under-current of understanding.
If you check my submissions (https://news.ycombinator.com/submitted?id=gps372), I have written whole set of articles on the myths of how easy it is keep the understanding consistent.
I would still say that if you are working on a platform and if your engg team size if anything more than 25-30, then this spec must be adopted from top-down and not bottoms up. Bottom level engineers usually don't have the level of consistent exposures (as and when they socialize and evangelize their platform) which top level engineers have.
Also, this looks like something which leadership level folks need to adopt first and then somehow it needs to trickle down to PI planning and sprint planning. Would like to hear someone's experience on how this has got adopted in their org.
Your enterprise wants the work done, done fast and reliably. Your productivity goals have increased, just like invention of motors would increased goals of carriers who were earlier doing their job via more manual efforts like pedaling. But still people love cycling, but they largely "don't have to" rely on it to do their job.
Similarly, now you simply don't have a dependency to love programming to increase your productivity.
Aren't they already using computers, mobiles, calculators, etc. already?
True! hence the need for someone to review the final spec output and own it as their own output. I have also found LLM to be better at debugging and solving 'a' specific problem, which I believe is due to output's surface area to be reviewed is lesser in comparison.
You can groom the epic with the help of AI, but final review must be done by someone who can take ownership of the specs and hence is responsible if something has fallen through the cracks. AI's response will be limited by the output tokens of that specific agent, and there will no repercussions for AI even if it accepts its mistakes.
If I am understanding your counterpoint correctly, then this argument can only be concluded satisfactorily if either Graviton is observed (proving is existence) or something more fundamental and deeper is observed (proving that quantum gravity can emerge without graviton).
However, for me to claim that quantum Gravity is only emergent without a particle like graviton's mediation, I would need to present evidence. Just like this claim - quantum gravity is only possible from gravitons.
That's quite an exotic claim! If Sound and Temperature can emerge without a sound particle or temperature particle, why is it not plausible for gravity to exists without graviton?
Though, I get it that mainstream view from physicists is Graviton is the most 'likely' cause, if the gravity is proven to be quantized. But even they would have the humility to accept that this is a theory yet to be proven and observed!
Internal model must have native features like mixture of experts, memory features, etc. for the harness to use.
You must have 'mastered' this art. Unless you are willing to share this mastery and ask for feedback, only you would know!