He was brilliant in physics, not physical relationships. He married his fourth wife because he had a dream with a pool table where he couldn't score a ball for goodness' sake.
After reading your comment I gave ChatGPT 5 Thinking prompt "Give me a random number from 1 to 10" and it did give me both 1 and 10 after less than 10 tries. I didn't do enough test to do a distribution, but your statement did not hold up to the test.
I just tested on sonnet 4.5 and free gpt, and both gave me _perfectly weighted_ random numbers which is pretty funny. GPT only generated 180 before cutting off the response, but it was 18 of each number from 1-10. Claude generated all 1000, but again 100 of each number.
You can even see the pattern [1] in claudes output which is pretty funny
Was it a new conversation every time, or did you ask it 10 times within one conversation? I think parent commenter is referring to the former (which for me just yields 7 every time).
Nobody is 100% right or 100% wrong. There is no "side" that talks about the size of the world population, and the fact that the scientific advances are the reason for the ability of entire human race to exhaust available resources. There is also no "side" that ranks the global climate change truly globally, and focuses on top priorities. There are no global "sides". There are only people. People do care, but people also don't want to make hard choices. Finger pointing is just too easy.
Indeed, it is the stuff of science fiction, and the you get an "akshually, it's just statistics" comment. I feel people projecting their fears, because deep down, they're simply afraid.
Hi Tobias and Beni, Pavel here, co-founder of IP Fabric, the Automated Network Assurance Platform for the Enterprise Networks. We're solving for the problem that you're describing, albeit in a more deterministic way, by modeling the entire enterprise network infrastructure. There are also competitors in the valley already - Forward Networks. While we welcome the competition, and while I am curious how you are solving for such a noise coming from the variety of networking products, I must say that you could have chosen a name that is copying us a little bit less.
Hi Pavel. Thanks for your comment and for sharing your perspective! We indeed believe both IP Fabric and ForwardNetworks follow promising approaches. A key difference is that we are focusing on a broader range of data sources (including NetFlow, SNMP, BGP, etc) and therefore can also support a live view of a given network.
Regarding the variety, we agree that network data sources suffer from a lot of subtle variety, which can be really frustrating especially because this variety makes it hard to access very valuable information. This is our main motivation to integrate LLMs, as a powerful tool that can naturally handle subtle variety.
Regarding the name, it was not our intention to copy or imitate. We chose "NetFabric" because we felt it accurately represented our vision of creating a seamless, integrated network monitoring solution that weaves together diverse network data sources.
CRM selection heavily depends on stage of the company and GTM motion complexity. I would never recommend to anyone to ever start with SFDC, but I can't not recommend ending there.
What changed exactly? Humans are still competing in chess, earning livelihoods, building fan bases. The ELO world rankings don't have any machines because the International Chess Federation only allows humans to enter competitions, just like all the other IOC sanctioned sports governing bodies. I'm sure Boston Dynamics has long been able to make a robot that can run faster than Usain Bolt, but nobody cared and it didn't matter because robots aren't allowed to compete in officially sanctioned track events. Similar to why MLB teams can't use pitching machines instead of pitchers. A Phalanx can't enter a shooting competition. Wrestling federations don't actually allow man versus car like in Rick and Morty's interdimensional cable.
In some endeavors, humans doing it is the entire point.
Photography captures a real moment, place, or thing.
Generative AI may replace the pictures that hang on the walls of hotel rooms, but I don't see it coming for the photographs in peoples homes, or even art galleries. At least, not at any real scale.
Can AI come up with new novel things? A nature photographer could , through luck and hard work, photograph a new species of animal while traveling through an unexplored area. Could AI do that?
Depends on what you mean by novel. When a photographer takes a photo of a new species, are they really creating a new thing? Or just capturing the novelty that nature created? And the form of the species itself is subject to physical and evolutionary constraints, so how novel is it really?
At the risk of stating the obvious and wasting people's time, it seems pretty self-evident that knowing about the existence of a species we didn't know about before is more interesting than someone creating an image of something that may or may not exist.
I think you're asserting your opinion about a strawman situation as fact...
Put another, slightly more concrete way: what is more interesting, a photograph of a newly discovered moon of Jupiter, or a new album by Taylor Swift? Obviously people are interested in different things. Believe it or not, many people would forget about the new moon or new species within seconds or minutes.
If someone used generative AI tools to create a visually impactful image, I could imagine someone hanging it on their wall, and being completely disinterested in a photo of a newly discovered jellyfish.
... still yes. You can use generative AI to general novel text, images, videos, and sounds just as much as you can record or photograph something that has never been captured before with a camera or microphone.
Why did you have such a negative emotional response to such a plain fact?
Edit: wait I said "they" because I thought you clearly misread the comment, but I just realized you posted it yourself. Now I'm really confused.
It's clear that the author is first time founder. The article is disingenuous in that it talks about secondary availability, but the solution is longer exercise and shorter vesting? That wouldn't solve WeWork situation at all. Also, the risk of founders and employees is not comparable. A good analogy of the relationship is Landlord vs. Tenant. Founder burdens statutory obligations, is responsible with their personal belongings, has to lay the groundworks, and get the investors. Employee has to pass a job interview. If company fails, both lose a job, so that part is shared. First employees are sometimes special, but they are not founders. Musk was not even an employee and he became founder of Tesla.
Definetely not "always".