LLMs

Document search and synthesis

Scores of organizations want to harness generative AI so employees can easily find the most relevant documents through improved search results and summaries. For example, your organization can reduce the time it takes employees to find answers to common HR- and process-related questions. Internal manuals and sites are... See more

Announcing Together Inference Engine – the fastest inference available

November 13, 2023・By Together

The Together Inference Engine is multiple times faster than any other inference service, with 117 tokens per second on Llama-2-70B-Chat and 171 tokens per second on Llama-2-13B-Chat

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Today we are announcing Together Inference Engine, the world’s... See more

You can think your way into solving a deterministic system, but you cannot think your way into solving a probabilistic system.

The first thing that I want to call out is that deterministic software has edge cases, while probabilistic software has long tails.

I find that a lot of junior folks try to really think hard about edge cases around... See more

1. You have access to a proprietary asset (like data) that others don’t have easy access to. In our “write job postings” example, perhaps you have a corpus of thousands of job postings including some outcome scores (as to how well they did). You could use this data to create better job postings. Others don’t have ready access to this data. Note: The

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We consider these aspects of our problem:

• Latency : How fast does the system need to respond to user input?


• Task Complexity : What level of understanding is required from the LLM? Is the input context and prompt super domain-specific?


• Prompt Length : How much context needs to be provided for the LLM to do its task?


• Quality : What is the acceptable

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To do this, we employ a technique known as AI-assisted evaluation, alongside traditional metrics for measuring performance. This helps us pick the prompts that lead to better quality outputs, making the end product more appealing to users. AI-assisted evaluation uses best-in-class LLMs (like GPT-4) to automatically critique how well the AI's... See more

We identified 30 types of tasks that UX professionals used generative AI tools for in their work. We grouped these tasks under four roles: content editor, research assistant, ideation partner, or design assistant.

• Content editor : Generating and editing text, from microcopy to social media posts, based on specifications or copy given by UX

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• Query the RAG anyway and let the LLM itself chose whether to use the the RAG context or its built in knowledge


• Query the RAG but only provide the result to the LLM if it meets some level of relevancy (ie embedding distance) to the question


• Run the LLM both on it's own and with the RAG response, use a heuristic (or another LLM) to pick the best answer

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Disruptive innovation comes in two flavors: (1) New-market disruption, where the company creates and claims a new segment in an existing market by catering to an underserved customer base, or (2) Low-end disruption, in which a company uses a low-cost business model to enter at the bottom of an existing market and claim a segment.

Copilots don’t... See more