Earlier quoted context omitted.
That's a tricky one though since the question is, is the air inside of the rubber duck part of the material that makes it? If you removed the air it definitely wouldn't look the same or be considered a rubber duck. I gave it to the bot since when taking ALL the material that makes it a rubber duck, it is less dense than water.
A rubber duck in a vacuum is still a rubber duck and it still floats (though water would evaporate too quickly in a vacuum, it could float on something else of the same density).
Gemini "duck" demo was not done in realtime or with voice
351–360 of 683 posts
Re: Gemini "duck" demo was not done in realtime or with voice
#352Earlier quoted context omitted.
Isn't it always easier to learn from others' mistakes? Google has the problem that it's typically the first to encounter a problem, and it has the resources to approach it (from search), but the incentive to monetize it (to get away from depending entirely on search revenue). And, management.
I don't know if that really excuses Google in this case because it's a productization problem. Google never tried to release a ChatGPT competitor until after OpenAI had. OpenAI has been wildly successful as the first mover, despite having to blaze some new product trails. Even after months of watching them and with near-infinite resources, Google is still struggling to catch up.
An AI product that makes search irrelevant is an existential threat, but I don’t think Google has the product DNA to pull off a replacement product for search themselves. I heard Google has been taken over by more business / management types, but it is still missing product as a core pillar.
Re: Gemini "duck" demo was not done in realtime or with voice
#353Re: Gemini "duck" demo was not done in realtime or with voice
#354A big red flag for me was that Sundar was prompting the model to report lots of facts that can be either true or false. We all saw the benchmark figures that they published and the results mostly showed marginal improvements. In other words, the issue of hallucination has not been solved. But the demo seemed to imply that it had. My conclusion was that they had mostly cherry picked instances in which the model happen…
These LLMs do not have a concept of factual correctness and are not trained/optimized as such. I find it laughable that people expect these things to act like quiz bots - this misunderstands the nature of a generative LLM entirely. It simply spits out whatever output sequence it feels is most likely to occur after your input sequence. How it defines “most likely” is the subject of much research, but to optimize for f…
Re: Gemini "duck" demo was not done in realtime or with voice
#355Earlier quoted context omitted.
Uhh, no, not really; quite the opposite in fact. Under Eric Schmidt they were engineer-driven, during the golden era of the 2000s. Nowadays they're MBA driven, which is why they had 4 different messaging apps from different product managers.
Lack of top-down direction is what allowed that situation. Microsoft is MBA-driven and usually has a coherent product lineup, including messaging. Also, "had." Google cleaned things up. They still sometimes do stuff just cause, but it's a lot less now. I still feel like Meet using laggy VP9 (vs H.264 like everyone else) is entirely due to engineer stubbornness.
Re: Gemini "duck" demo was not done in realtime or with voice
#356This is so crazy. Google invented transformers which is the bases for all these models. How do they keep fumbling like this over and over. Google Docs created in 2006! Microsoft is eating their lunch. Google creates the ability to change VM's in place and makes a fully automated datacenter. Amazon and Microsoft are killing them in the cloud. Google has been working on self driving longer than anyone. Tesla is catchin…
I was with you until the Tesla hot take. I'd bet dollars to donuts that Tesla doesn't get to level 4 by the end of the decade. Waymo is already there.
Re: Gemini "duck" demo was not done in realtime or with voice
#357I have used Swype texting since the t9 days. If I demoed swype texting as it functions in my day to day life to someone used to a querty keyboard they would never adopt it The rate at which it makes wrong assumptions about the word, or I have to fix it is probably 10% to 20% of the time However because it’s so easy to fix this is not an issue and it doesn’t slow me down at all. So within the context of the different…
Its honestly pretty mind boggling that we’d even use querty on a smartphone. The entire point of the layout is to keep your fingers on the home row. Meanwhile people text with a single or two thumbs 100% of the time.
Re: Gemini "duck" demo was not done in realtime or with voice
#358This is so crazy. Google invented transformers which is the bases for all these models. How do they keep fumbling like this over and over. Google Docs created in 2006! Microsoft is eating their lunch. Google creates the ability to change VM's in place and makes a fully automated datacenter. Amazon and Microsoft are killing them in the cloud. Google has been working on self driving longer than anyone. Tesla is catchin…
A product requires commitment, it requires grind. That 10% is the most critical one, and Google persistently refuses to push products across the finish line, just giving up on them and adding to the infamous Google Product Graveyard.
Honestly, what is the point? They could just maintain the core search/ads and not pay billions of dollars for tens of thousands of expensive engineers who have to go through a bullshit interview process and achieve nothing.
Re: Gemini "duck" demo was not done in realtime or with voice
#359Earlier quoted context omitted.
I’m not an expert but I suspect that this aspect of lack of correctness in these models might be fundamental to how they work. I suppose there’s two possible solutions: one is a new training or inference architecture that somehow understand “facts”. I’m not an expert so I’m not sure how that would work, but from what I understand about how a model generates text, “truth” can’t really be a element in the training or i…
> this aspect of lack of correctness in these models might be fundamental to how they work. Is there some sense in which this isn't obvious to the point of triviality? I keep getting confused because other people seem to keep being surprised that LLMs don't have correctness as a property. Even the most cursory understanding of what they're doing understands that it is, fundamentally, predicting words from other words…
Modern machine learning models contain a lot of inscrutable inner layers, with far too many billions of parameters for any human to comprehend, so we can only speculate about what's going on. A lot of people think that, in order to be so good at generating text, there must be a bunch of understanding of the world in those inner layers.
If a model can write convincingly about a soccer game, producing output that's consistent with the rules, the normal flow of the game and the passage of time - to a lot of people, that implies the inner layers 'understand' soccer.
And anyone who noodled around with the text prediction models of a few decades ago, like Markov chains, Bayesian text processing, sentiment detection and things like that can see that LLMs are massively, massively better than the output from the traditional ways of predicting the next word.
Re: Gemini "duck" demo was not done in realtime or with voice
#360This is so crazy. Google invented transformers which is the bases for all these models. How do they keep fumbling like this over and over. Google Docs created in 2006! Microsoft is eating their lunch. Google creates the ability to change VM's in place and makes a fully automated datacenter. Amazon and Microsoft are killing them in the cloud. Google has been working on self driving longer than anyone. Tesla is catchin…
I was with you until the Tesla hot take. I'd bet dollars to donuts that Tesla doesn't get to level 4 by the end of the decade. Waymo is already there.