welcome to long field of view— where I perused the news of the week and stripped it down to the nitty-gritty.let’s work out what is really important.
This week: Sources say this is the open source future of OpenAI, with Mojo boosting AI performance.
1. Rumors of OpenAI FOSS LLM
First article of the week: An anonymous source told us informationJon Victor of said that OpenAI plans to release an open-source version of its Large Language Model (LLM).but does it make sense?
Analysis: Elon goes his own way
Iron Man brought up his own old story on CNBC. He talks about how he funded OpenAI in the early days (although the amount seems to have halved from $100 million to just $50 million for him). But the bottom line, he stressed, is that OpenAI should be: Open. in particular, open source nonprofit.
Ananya Mariam Rajesh: OpenAI Prepares New Open Source AI Models… Report
OpenAI prepares new open source language model for general availability [said] someone who knows the plan. …OpenAI is unlikely to release a model that competes with GPT, the report says.
Usama Jawad: Following ChatGPT’s success, OpenAI may release open-source AI models
OpenAI, creator of ChatGPT, is considering releasing a new open-source AI model soon, according to a new report. … He, the Large Language Model (LLM) behind ChatGPT, said this would be a significant development considering GPT-4 is closed source.
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If the latest rumors are to be believed, OpenAI is about to change course and release a publicly accessible alternate version of GPT-4. … Now OpenAI charges customers $20/month [for] ChatGPT Plus with GPT-4.
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Other players are already making waves in this area. Meta released its open-source Large Language Model Meta AI (LLaMA) a few months ago. Even the smallest variant of the model has been trained with over 1 trillion tokens, giving researchers and hobbyists a huge playing field to explore and even improve the underlying technology. Perhaps OpenAI has a similar idea.
Who would put this into context? Can Will Douglas be in heaven?
Last week, a leaked memo… reportedly written by a senior Google engineer, said out loud what many in Silicon Valley must have been whispering for weeks: Open source free giveaways are big. It threatens tech’s AI dominance.
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Open-source large-scale language models are being dropped like candy from piñatas: … HuggingChat … StableLM … Alpaca … Dolly … Cerebras-GPT.
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The future of how AI is created and used is at a crossroads. … In many ways, that’s a good thing. Easier access to these models will drive innovation and help find flaws in them. AI will not thrive if only a few large, wealthy corporations control this technology or decide how it is used.
It’s all Elon’s fault. Musk told David Faber:
I fully admit to being an idiot. … I am the reason OpenAI exists. …Hey, fate likes sarcasm – next level. …doesn’t exist without me.
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I came up with a name.name Open AI refers to open source. The intent was, “What’s Google’s opposite?” It will be an open source non-profit organization.
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Is it legal to set up a company as a non-profit, take its intellectual property, transfer it to a for-profit organization, and then make a huge profit out of it? …which is the exact opposite of what I gave you money for . …I worry that Microsoft actually has more control than …the OpenAI leadership team realizes.
It resonates with nr2x:
These tools are the result of decades of government-funded academic research and driven by decades of user-generated content as well. …Corporate AI is only raising the price of public goods and he is selling back 90%. Should be legally forced to open source.
On the other hand, u/wencc points out that the hint is in the name.
So, does OpenAI make AI open?
2. Mojo Raisin
Mojo, a compiled superset of Python, of A language for AI. Most models are now coded in Python, terrifyingly slow.
The Analysis: If Anyone Can Do It, So Can Ratner’s Team
Chris Lattner, creator of Swift, MLIR, and LLVM, co-founded Modular, the company behind Mojo.Therefore, I think it can be assumed that it is not night flight operations.
Jeremy Howard: Mojo may be the biggest programming language advancement in decades
Almost all AI models are now developed in Python, thanks to its flexible and elegant programming language, amazing tools and ecosystem, and high-performance compiled libraries. …but Python is thousands of times slower than languages like C++.
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Mojo is Python. …It might be better to say that Mojo is Python++. … A key Mojo trick is that as a developer you can always opt-in to a faster “mode” by using “fn” instead of “def” when writing functions. In this mode, all variable types must be declared accurately so that Mojo can create optimized machine code for implementation. [it]. Using “structs” instead of “classes” also allows you to use attributes inside data structures without chasing pointers, as the attributes are tightly packed in memory. These are the kinds of features that enable speedups in languages like C and are now available to Python programmers.
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At its core is MLIR, which has been in development for many years and was originally developed by Chris Lattner at Google. He saw what was needed for the core foundation of a “programming language for the AI age” and focused on building it. [There’s] This is why I am optimistic about Mojo’s future. The project is still in its early stages, but my guess is… it will develop further and faster than most of us expect.
he is shining His name is Jeff Delaney.
Python is a great language for productive programming, but it has one big problem: it’s too slow. And being slow means being teased by Rust and C++ chads all over the world. … mojo [is] A superset of Python, up to 35,000 times faster than Grandpa Python. … Here are five things you need to know.
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1. This is not a random person’s side project on GitHub, it’s from a company founded by the people who created the Swift programming language and the LLVM compiler tool chain. If anyone can solve your Python problems, it’s him.
2. It is a language designed for programming on AI hardware such as GPUs running Cuda and other accelerators. This is achieved without much complexity by leveraging and extending the Multilevel Intermediate Representation (MLIR). In addition, it also has built-in automatic tuning to optimize your code. …
3. Designed to be a superset of Python in the same way that TypeScript is a superset of JavaScript.So no need to learn another language [and] You can still use your favorite libraries like numpy, pandas, etc.
4. Adds strong type checking and error checking for memory management. It has a Rust-like ownership system and borrow checker, and also supports manual memory management using C++-like pointers. It’s a pragmatic language that provides security, but also the flexibility to become less secure if necessary. …
5. Currently closed to the public. Still in early stages of development. It will be open sourced in the future, but currently has a trial waiting list. We were lucky enough to get early access, so let’s get started:
hang on. pause. 35,000x performance? Get off my lawn, prompts Monkey Express.
This is no good either. …just need someone who knows a little bit about how the hardware works. Attempting to “solve” this ignorant problem with fancy solutions is unlikely to work very well. …I don’t understand why it’s so hard to learn the basics of CPU/GPU architecture. This is not impossible if you are doing serious AI research.
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Similar ignorance is found in a lot of JavaScript. Ignoring the underlying hardware can completely destroy modern CPUs doing very simple things, but on the other hand code that can run very well with a little respect can be written Unfortunately… ignorance is bliss for most developers.
The moral of this story:
If they say I never loved you, you know they’re liars
— Jim Morrison
you are reading long field of view By Rich Jennings. You can contact him at: @RiCHi or tlv@richi.uk.
Image: Dollar Gill (via Unsplash, leveled and cropped)
