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My journey with GPT-4 as a novice programmer has been nothing short of remarkable. I used it to write a game, and despite my limited programming knowledge, I was astonished by the results.
It makes coding suggestions, completes my code, and even identifies bugs, which has been a game-changer for me. It feels like having a co-programmer who anticipates my needs and guides me in the right direction.
When I started using ChatGPT in november of 2022, it was very smart. I used it quite a lot to help me rephrase my emails better, to tidy up my writing, to do some simple math that I'm too lazy to do myself, etc. But recently I noticed that it has become less and less helpful, it does things that I specifically asked it NOT to do, it struggles to rephrase my texts the way I want it to, it makes mistakes in basic math and provides all sorts of incorrect information. Now it annoys me way more than it helps me.
ChatGPT is a powerful, open-source language model AI tool, very fastly response query to users.
Based on our record, ChatGPT seems to be a lot more popular than Vectara Neural Search. While we know about 815 links to ChatGPT, we've tracked only 13 mentions of Vectara Neural Search. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
By following these steps, developers can train ChatGPT on their own data. This will allow to give personalized, accurate, and domain-specific responses. Keep in mind that this process requires technical skills and can take more time than using no-code platforms. - Source: dev.to / 17 days ago
ChatGPT prompt: Act like a senior software developer mentor. Explain to me in the simplest way possible what javascript Symbols are, making very basic examples that DO NOT use "foo" "bar" words. Make small sentences and ask me often if I am able to understand. Thank you. - Source: dev.to / 17 days ago
AI and LLMs such as ChatGPT are amazing at what they do, but they suffer from the lack of "an opposable thumb", to use an analogy. This implies that as stand alone products, they can't really do much, if anything at all. - Source: dev.to / 22 days ago
Prompt Engineering is the art of instructing an LLM such as ChatGPT to do what you want it to do, using nothing but natural language, logic, and reason. The process is probably easily within reach of 80% of the world's population, while less than 0.3% of the world's population knows how to code. - Source: dev.to / 24 days ago
"ChatGPT" in this case means the frontends https://chat.openai.com and https://chatgpt.com, not the API. - Source: Hacker News / 26 days ago
Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application. - Source: Hacker News / 4 months ago
You should also check us out (https://vectara.com) - we provide RAG as a service so you don't have to do all the heavy lifting and putting together the pieces yourself. Source: 7 months ago
Hi HN! I lead product for Vectara (https://vectara.com) and we recently worked with OpenSource connections to both evaluate our new home-grown embedding model (Boomerang) as well as to help users start more quantitatively evaluating these systems on their own data/with their own queries. OSC maintains a fantastic open source tool, Quepid, and we worked with them to integrate Vectara (and to use it to... - Source: Hacker News / 9 months ago
RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just choosing a vector DB (last time I checked there were about 50), managing it, deciding on how to chunk data, etc. You also need to ensure your retrieval pipeline is accurate and fast, ensuring data is secure and private, and manage the whole thing as it... - Source: Hacker News / 10 months ago
I agree. My experience is that hybrid search does provide better results in many cases, and is honestly not as easy to implement as may seem at first. In general, getting search right can be complicated today and the common thinking of "hey I'm going to put up a vector DB and use that" is simplistic. Disclaimer: I'm with Vectara (https://vectara.com), we provide an end-to-end platform for building GenAI products. - Source: Hacker News / 10 months ago
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