The last time I checked (a few days ago) it only had an "Upload Image" option... and I have been playing with Gemini on and off for months and I have never been able to actually upload an image.
It's basically what I've come to expect from most Google products at this point: half-baked, buggy, confusing, not intuitive.
There's not a lot of detail in the announcement but I assume this is some kind of RAG system. I wonder if it will cover some short time period (past week, past month?) or if they are trying to cover the whole time period since the knowledge cutoff of the current model.
What mechanism would make it possible to enforce non-paywalled, non-authenticated access to public web pages? This is a classic "problem of the commons" type of issue.
The AI companies are signing deals with large media and publishing companies to get access to data without the threat of legal action. But nobody is going to voluntarily make deals with millions of personal blogs, vintage car forums, local book clubs, etc. and setup a micro payment system.
Any attempt to force some kind of micro payment or "prove you are not a robot" system will add a lot of friction for actual users and will be easily circumvented. If you are LinkedIn and you can devote a large portion of your R&D budget on this, you can maybe get it to work. But if you're running a blog on stamp collecting, you probably will not.
Whenever I see one of these posts, I click just to see if the proposed solution to testing the output of an LLM is to use the output of an LLM... and in almost all cases it is. It doesn't matter how many buzzwords and acronyms you use to describe what you're doing, at the end of the day it's turtles all the way down.
The issue is not the technology. When it comes to natural language (LLM responses that are sentences, prose, etc.) there is no actual standard by which you can even judge the output. There is no gold standard for natural language. Otherwise language would be boring. There is also no simple method for determining truth... philosophers have been discussing this for thousands of years and after all that effort we now know that... ¯\_(ツ)_/¯... and also, Earth is Flat and Birds Are Not Real.
Take, for example, the first sentence of my comment: "Whenever I see one of these posts, I click just to see if the proposed solution to testing the output of an LLM is to use the output of an LLM... and in almost all cases it is." This is absolutely true, in my own head, as my selective memory is choosing to remember that one time I clicked on a similar post on HN. But beyond the simple question of if it is true or not, even an army of human fact checkers and literature majors could probably not come up with a definitive and logical analysis regarding the quality and veracity of my prose. Is it even a grammatically correct sentence structure... with the run-on ellipsis and what not... ??? Is it meant to be funny? Or snarky? Who knows ¯\_(ツ)_/¯ WFT is that random pile of punctuation marks in the middle of that sentence... does the LLM even have a token for that?
If you're running a company that is paying multiple vendors for basic AI features and LLM functionality, it might be worth doing the calculation of how much of that functionality might be covered by getting all of your employees on iOS and MacOS...
There are lots of valid use cases for speech synthesis and text-to-speech technology, and there are like 1 or 2 valid/legal use cases for voice cloning that I can think of. Ignoring the moral and ethical questions, why would anybody devote time and resources building a company around a very niche solution... one in which your customer churn rate is partially dependent on users not ending up in prison.
Had to chuckle when I looked at the Digital Advertising Alliance WebChoices browser tool (in Safari or any browser with cross-site tracking disabled). It allows you to opt out of being tracked, as long as you enable cross-site tracking and let them add a cookie. ¯\_(ツ)_/¯
1. If you have capital to invest, you could do worse than AI startups at the moment.
2. Nvidia's long-term threat is not just direct competitors (AMD, Intel), but the big cloud-players going to in-house chips. Supporting the next wave of your customers makes sense.
3. Using Nvidia is the path of least resistance right now. If you only invest in startups using your products (and you are an active investor), you give startups another reason to avoid taking a risk on the alternative.
Ignoring the obvious issue that this whole anonymous story seems suspiciously perfect for selling a related product...
On the one hand...
Companies spent the past couple of decades engaging in various SEO hacks to rank high on search results and OpenAI scraped the internet to train a language model. Theoretically, it seems possible that some of the SEO techniques at least partially colored the flavor of LLM-generated text, and an "AI detector" could pick that up. So if you do a great job writing SEO optimized text (wordy, structured, lots of repeated key words, etc.) you are more likely to be flagged.
But really..
"AI Detector" services are snake oil and will lead to the creation of "Anti AI Detector" services that offer protective spells against the original snake oil. See, we eliminate a bunch of jobs with AI but we create whole new disciplines of work that didn't exist before. "AI Generated Content Obfuscation Specialist - III - W2" coming to a job board near you soon.
I've been thinking along the same lines. The token window IMO should be a conceptual inverted pyramid, where there most recent tokens are retained verbatim but previous iterations are compressed/pooled more and more as the context grows. I'm sure there's some effort/research in this direction. It seems pretty obvious.
I think the claim is based on the public political statements made by leaders in Texas. The fact that there is a huge discrepancy in what they say publicly against the science of global warming and the utility of renewables versus what the investment numbers say is the really sad part. Basically it boils down to: I'm going to lie through my teeth to pander to the stupid people who vote for me, but I'm also going to create favorable conditions for my wealthy buddies to make a killing in renewables.
When people are faced with negative outcomes resulting from things they approve of, they do this passive-aggressive bit where they pretend to have a valid point.
I used to buy into some of this JFK stuff when I was a X-Files watching teenager. What really burst the bubble for me was a documentary I watched where a team of snipers and forensic scientists re-created the exact shot with mannequins with bones and ballistic gel. They didn't even have to try that hard. Using the same rifle and ammo, the first shot they tried resulted in almost the same exact trajectory. I can't find a clip of that exact documentary (circa 2004-2006), but there are others who have done the same. You don't have to look hard to find very comprehensive and scientific explanations for the exact trajectory of that specific shot. But you do have to look very hard to find an actual explanation for why it is impossible that is beyond the level of "golly gee folks, I done shot lots of guns in my life and let me tell you, it ain't possible."
I dabble in music production and know some of the people in the "Lofi" world, so I know for a fact that this is not true. It's just a formulaic sub-genre where people are trying to make similar instrumentals with the same vibe. It would be jarring to listen to a playlist while studying and each song had wildly different tempos, instruments, etc.
Also, the music doesn't sound "Lofi" because it's generated by algorithms. A lot of hard work and software goes into taking a clean, pitch-perfect digital signal and making it sound like something playing on a record player from the 70s.
First of all, I'd like to say that this looks like a great project and I wish you the best of luck. I've done a bit of work on building knowledge graphs from semi-structured data and I know that every aspect of it is challenging. Obviously there's the data pipelines, ETL, semantic matching/categorization, statistical models, etc. Just building a simple UI for presenting a large knowledge graph was more challenging than most front end work I've ever done.
Question: if the goal is to build a knowledge graph that can "explain how anything in the world is related to everything else" how do you measure progress toward that goal? And how do you measure the quality? Just having a bunch of topics and relationships is not a great metric in my opinion. Obviously this is still very early, but here's an example I found in about 30 seconds of clicking around:
> Remember, Stephenson’s target audience consisted of “scientists, mathematicians, engineers, and entrepreneurs.” Given his choice to court private wealth, it’s no surprise that Project Hieroglyph was doomed from the start. After all, you can’t very well expect to succeed as a hero if you stop to ask the villains for their permission.
It's really, really hard to take somebody serious when their political frame of reference makes them see the world in such crisp black and white contrast they just assume, without any further explanation needed, that clearly everybody already agrees that entrepreneurs (or maybe private wealth? As in, non-government wealth?) are the real villains.
It's basically what I've come to expect from most Google products at this point: half-baked, buggy, confusing, not intuitive.