He puts into clear terms what had previously been an unarticulated, creeping suspicion I had about #GenAI. Clearly there are many angles from which to come at what's going on with #AI#hype , but I appreciate this one quite a bit.
I don't personally think LLMs will ruin everything, but neither do I think they will solve everything. Despite being in the tech world, I've been skeptical of many of the applications in which they've made an appearance in the past 18 months.
This is the cherry on top. You can no longer avoid it if you're a Google user. And even worse, its hallucinations will displace reliable but smaller sources of info.
The white background logo is the current hex sticker for my TidyDensity #R#package the others were generated from DALL-E #dalle3#gpt#chatgpt pretty cool
GPT4O combines audio, image, text. It can analyze actual audio. Also you can interrupt voice. It can pick up emotion from audio. You can also ask different speech with diffetrent style including singing! It can see the image in real time and chat on voice. For example solving equation in real time as you write on paper. This is amazing! #LLM#AI#GPT#ML#OpenAI
Like many other technologists, I gave my time and expertise for free to #StackOverflow because the content was licensed CC-BY-SA - meaning that it was a public good. It brought me joy to help people figure out why their #ASR code wasn't working, or assist with a #CUDA bug.
Now that a deal has been struck with #OpenAI to scrape all the questions and answers in Stack Overflow, to train #GenerativeAI models, like #LLMs, without attribution to authors (as required under the CC-BY-SA license under which Stack Overflow content is licensed), to be sold back to us (the SA clause requires derivative works to be shared under the same license), I have issued a Data Deletion request to Stack Overflow to disassociate my username from my Stack Overflow username, and am closing my account, just like I did with Reddit, Inc.
The data I helped create is going to be bundled in an #LLM and sold back to me.
In a single move, Stack Overflow has alienated its community - which is also its main source of competitive advantage, in exchange for token lucre.
Stack Exchange, Stack Overflow's former instantiation, used to fulfill a psychological contract - help others out when you can, for the expectation that others may in turn assist you in the future. Now it's not an exchange, it's #enshittification.
Programmers now join artists and copywriters, whose works have been snaffled up to create #GenAI solutions.
The silver lining I see is that once OpenAI creates LLMs that generate code - like Microsoft has done with Copilot on GitHub - where will they go to get help with the bugs that the generative AI models introduce, particularly, given the recent GitClear report, of the "downward pressure on code quality" caused by these tools?
While this is just one more example of #enshittification, it's also a salient lesson for #DevRel folks - if your community is your source of advantage, don't upset them.
Strong agree. A lot of Elinor Ostrom's work around governance of the commons - where we get the phrase "tragedy of the commons" - relied on mechanisms of co-operation between institutions.
One of the key challenges I see here is that corporations like OpenAI now have a lot more power than even groups of institutions - lawmakers, governments, civil society. We've seen that recently with the way Meta has influenced government policy around paying to share content from commercial news agencies.
There's also a paradox here - an increased production of work in the Commons is good for OpenAI - because it provides them with more data. However, the way in which the Commons is used - to create for-profit products like #GPT, serves as a constraint on people donating creative material to the commons.
In #homeassistant, using #nodered to make an API call to a #llamacpp server running #mistral 7B model. I create a prompt that asks it to summarize all the data in my house from the sensors. The results are pretty impressive for such a little model. Now I get a customized rundown, Jarvis style.
Useful? Probably not. But cool as hell. :cool_skelly:
Było ujęcie, że inteligencja to jest zdolność rozwiązywania problemów.
Ale można też po prostu znać gotowe rozwiązania problemów, po prostu wyuczone, wtedy wystarczy podążać ścieżką według gotowego rozwiązania, wyciągniętą z pamięci.
Jest ujęcie, że inteligencja, to jest dobra kompresja danych, że sztuczna inteligencja to też na tym polega, tak powstaje model. A kompresja, to po prostu odnalezienie analogii, żeby móc coś upakować w mniejszym rozmiarze.
W mózgu też tak to działa.
Jakby to pociągnąć, to wyobraź sobie rozpakowane dane, z bardzo inteligentnego mózgu/modelu. To by była masa gotowych rozwiązań problemów, do każdej możliwej sytuacji.
Po tym rozwiązanie problemu, to już nie inteligentne myślenie, tylko przelecenie po (tych rozpakowanych) w pamięci gotowych rozwiązań, i zastosowanie ich.
Czyli ostatecznie wszystko sprowadziłoby się do zastosowania gotowych rozwiązań problemów, trzeba tylko zestawić problem z rozwiązaniem, i gotowe.
Inteligencja teoretycznie tworzy coś na poczekaniu, ale można spojrzeć na inteligencję w ten sposób, że to i tak jest lecenie sobie gotowymi rozwiązaniami, gotowymi ścieżkami. #artificialintelligence#ai#inteligencja#mozg#iq#gpt
If you compare the difference between now freely available LLMs like GPT 3.5, Claude Sonnet, LLM3 etc with the paid versions of various models, the difference for most ordinary users/usecases is quite small. That must be a problem for the businesscase of companies like OpenAI, they need large numbers of ordinary people willing to pay every month for access to their models, if you look at the enormous investments? Or are other revenue streams more important ? 🤔 #AI#businessmodels#LLM#GPT
OpenAI’s New GPT-4o Model Revolutionizes AI Landscape, Draws Mixed Reviews (articleshubspot.com)
The GPT-4o Model is an upgraded version of the highly successful GPT-4, which has been widely used in OpenAI's flagship product, ChatGPT.