Nicolay Gerold

As for your business idea, start small and test things out. Don’t just quit your job and jump into “doing business.” I hastily did that once when I was younger and failed miserably. But I also had enough time to recover. In that process, I learned a ton, which helped me immensely with my current situation. But in retrospect, that came with the... See more

Before we know it, saying a product “uses AI” will seem as silly and obvious as saying a product “uses a database.” Today, the average developer might not know how a query planner works, but they definitely use a database. Similarly, we don’t expect the average developer in five years to know how a transformer works. But we guarantee they will know... See more

“I think a lot of people obviously want to talk about the sexy kind of new consumer applications. I would tell you that I think that the earliest and most significant effect that AI is going to have on our company is actually going to be as it relates to our developer productivity. Some of the tools that we’re seeing are going to allow our devs to... See more

• LLM Pro/Serious Use Comparison/Test: From 7B to 70B vs. ChatGPT! Winner: Synthia-70B-v1.2b


• LLM Chat/RP Comparison/Test: Dolphin-Mistral, Mistral-OpenOrca, Synthia 7B Winner: Mistral-7B-OpenOrca


• LLM Chat/RP Comparison/Test: Mistral 7B Base + Instruct


• LLM Chat/RP Comparison/Test (Euryale, FashionGPT, MXLewd, Synthia, Xwin) Winner: Xwin-LM-70B-V0.1


• New

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Google Deepmind used similar idea to make LLMs faster in Accelerating Large Language Model Decoding with Speculative Sampling. Their algorithm uses a smaller draft model to make initial guesses and a larger primary model to validate them. If the draft often guesses right, operations become faster, reducing latency.

There are some people speculating... See more

In general, I see LLMs to be used in two broad categories: data processing, which is more of a worker use-cases, where the latency isn't the biggest issue but rather quality, and in user-interactions, where latency is a big factor. I think for the faster case a faster fallback is necessary. Or you escalate upwards, you first rely on a smaller more... See more

1. Scalability is crucial - systems need to be designed with the assumption that query volume, document corpus size, indexing complexity etc. could increase by 10x. What works at one scale may completely break at a higher scale.


2. Sharding the index, either by document or by word, is important to distribute the indexing and querying load across machines.

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Kids:- Secure attached.- Avoidant.- Ambivalent: reactions are inconsistent, wanted to bond but annoyed.- Disorganized: avoided interaction and fearful upon return of caregiver.