Meta’s Coding Version of Llama-2
Plus: Hugging Face's $235M funding & its SafeCoder.
Hello, Engineering Leaders and AI Enthusiasts!
Welcome to the 93rd edition of The AI Edge newsletter. This edition brings you Meta’s coding version of Llama-2, Code Llama.
And a huge shoutout to our amazing readers. We appreciate you😊
In today’s edition:
🤖 Meta’s coding version of Llama-2
🔥 Google, Amazon, Nvidia, and others pour $235M into Hugging Face
🚀 Hugging Face’s Safecoder lets businesses own their own Code LLMs
🧠 Knowledge Nugget: How urgent is GenAI for me and my firm (or my investments) to understand now? by
Let’s go!
Meta’s coding version of Llama-2
Meta has released Code Llama, a state-of-the-art LLM capable of generating code and natural language about code from both code and natural language prompts. It is free for research and commercial use. It can also be used for code completion and debugging and supports many of the most popular languages today, including Python, C++, Java, PHP, Typescript (Javascript), C#, and Bash.
Code Llama is built on top of Llama 2 and is available in three models:
Code Llama, the foundational code model;
Codel Llama - Python specialized for Python;
and Code Llama - Instruct, fine-tuned for understanding natural language instructions.
It is releasing in three sizes with 7B, 13B, and 34B parameters. Meta’s benchmark testing showed that Code Llama performed better than open-source, code-specific LLMs and outperformed Llama 2. However, it seems there was no 70B variant released.
Why does it matter?
Coding tasks were not Llama’s strong suit. But this iteration of the Llama family (Code Llama - Python 7B) outperforms Llama 2 70B. The 34B model is also twice as good as the 70B Llama 2 model, closes the gap to (the much larger) GPT 4, and outperforms GPT 3.5.
It can make workflows faster and more efficient for current developers, lower the entry barrier for people learning to code, and spur a new wave of experimentation in AI and programming.
(Source)
Google, Amazon, Nvidia, and others pour $235M into Hugging Face
The open-source AI model repository got massive investments from Google, Amazon, Nvidia, and Salesforce as demand for AI model access grows. Other investors included AMD, Intel, Qualcomm, and IBM, all of whom also have invested significantly into generative AI foundation models or processors running these models.
This latest financing brings Hugging Face’s valuation to $4.5 billion. The funds will be used to grow the team, currently at 170, and invest in more open-source AI and platform building.
Why does it matter?
Such huge investments underscore the importance of the open-source community in building up the generative AI community. It also reflects the enormous appetite for AI and platforms to support its development. This will benefit the broader open-source AI ecosystem and companies who want to build AI themselves.
(Source)
Hugging Face’s Safecoder lets businesses own their own Code LLMs
Hugging Face has launched SafeCoder, a code assistant solution built for the enterprise. It is a complete commercial solution, including service, software, and support.
For enterprises, the ability to tune Code LLMs on the company code base to create proprietary Code LLMs improves the reliability and relevance of completions to create another level of productivity boost. However, relying on closed-source Code LLMs to create internal code assistants exposes companies to compliance and security issues.
With SafeCoder, Hugging Face will help customers build their own Code LLMs, fine-tuned on their proprietary codebase, using state-of-the-art open models and libraries, without sharing their code with Hugging Face or any other third party.
Why does this matter?
This allows organizations to leverage the most advanced but closed-sourced AI models securely. This can enhance the adoption of AI, especially in industries where data protection is paramount.
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Knowledge Nugget: How urgent is GenAI for me and my firm (or my investments) to understand now?
have insightfully answered some of the most common questions about AI from investors and executives.For this one (Question 2 of 7),
recommends “if a large part of your cost base is paying talent who manipulate words, images, numbers and/or sounds for their work – what we call “WINS” work– then it is urgent that your organization look into Generative AI immediately.”In the article, he also lists the significant AI investments, industries AI will change fundamentally, and business functions AI has already changes or is currently changing.
Why does this matter?
The article gives a clear, practical picture for you to decide how urgent Generative AI is for your organization and help adapt to the transformative changes happening across industries and business functions. Moreover, it helps make informed investment decisions in AI.
What Else Is Happening❗
🚀OpenAI partners with Scale to provide support for enterprises fine-tuning models (Link)
📌Ex-Pinterest staffer launches AI app to beat Pinterest, raises $5 Million (Link)
📺Amazon brings new AI-driven features to Thursday Night Football on Prime Video (Link)
🌐Britain to host world’s first AI safety summit at home of World War II codebreakers (Link)
💰Modular secures $100 Million to build tools to optimize and create AI models (Link)
🌟📝Friday Featured Prompt
This Week's Prompt: Create UX Process For a Specific App Or Website
As an experienced UX designer, create a comprehensive UX process for a specific app or website, taking into account the following aspects: App/Website: [App/Website Name] Target Audience: [Describe Target Audience] Project Timeline: [Specify Project Timeline] Research Methods: [List Research Methods, e.g., Surveys, Interviews, Competitor Analysis] Design Tools: [List Design Tools, e.g., Sketch, Figma, Adobe XD] Core Business Goals: [Goal] Core User Goals: [Goal] Deliverable: Based on the information provided, create a detailed UX-process outlining all the steps that need to be taken to create an optimal product that will maximise sign ups, engagement, and revenue. This UX process should be tailor made for this specific app / website based on the information I have provided. Provide estimated timings for each task together with recommended title of person(s) required to complete the tasks.🦸This prompt is your trusty sidekick for a breezy design journey.
You can dive straight into what you love– crafting a stunning app or website. Let AI take care of the nitty-gritty details and craft a roadmap for the next big thing so that you can unleash your creativity without hitches.
Say farewell to the tedium of planning and researching– Design Smarter, Not Harder!
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That's all for now!
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