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- OpenAI data leak leads to firings 🔥
OpenAI data leak leads to firings 🔥
LLMs vs SLMs, Meta's new AI chip, Apple's AI plan causes stock surge, and more!
Everyday AI
April 12, 2024
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Outsmart The Future
Today in Everyday AI
6 minute read
🎙 Daily Podcast Episode: Everyone seems to be making the push from large language models to small language models. But what are they? Here’s what you should know. Give it a listen.
🕵️♂️ Fresh Finds: Cathie Wood’s takes stake in OpenAI, Meta testing its AI chatbot on social media, and how a drone company uses AI to help farmers. Read on for Fresh Finds.
🗞 Byte Sized Daily AI News: OpenAI data leak leads to firings, Meta announces new AI chip, Adobe's Firefly AI model trained on Midjourney images, and Apple’s new AI plan. For that and more, read on for Byte Sized News.
🚀 AI In 5: We stumbled upon a custom GPT that’s perfect for verifying emails for cold outreach. See it here
🧠 Learn & Leveraging AI: Confused about small language models? Here’s what to know and how they differ from LLMs. Keep reading for that!
↩️ Don’t miss out: Did you miss our last newsletter? We talked about GPT-3.5 vs GPT-4, Google Photos AI editing features, and Amazon’s CEO sharing their AI plan. Check it here!
Small Language Models: What they are and do we need them? 🤔
It seems like we just started to understand large language models.
LLMs are extremely powerful and can do just about anything.
Buuuuut there’s a new kid on the block.
Enter small language models.
All the talk now is about small language models. So what are they and how do they compare to LLMs?
We explain small language models and their future.
Join the conversation and ask Jordan questions on small language models here.
Also on the pod today:
• Advantages & Usage of Small Language Models ✅
• Comparison of Small & Large Language Models 🥊
• Future of Small Language Models 💭
It’ll be worth your 31 minutes:
Listen on our site:
Click to listen
Subscribe and listen on your favorite podcast platform
Listen on:
Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – ChapterOne is an AI resume analysis, Dovetail turns customer data into insights, and Humanizer is an AI voice platform.
Trending in AI – Cathie Wood′s Ark Invest has taken a stake in OpenAI.
Big Tech - Meta is testing its AI chatbot in India and Africa across WhatsApp, Instagram, and Messenger.
AI in Society - This drone company is using AI to help US farmers.
Future of Work – Big banks on Wall Street are considering reducing junior analysts by up to two-thirds for AI instead.
1. OpenAI Fires Researchers Over Alleged Information Leak 🔥
According to a report from The Information, OpenAI has dismissed two researchers, Leopold Aschenbrenner and Pavel Izmailov, for suspected information leaks.
Aschenbrenner, known for his work on AI safety, was reportedly aligned with OpenAI's chief scientist, Ilya Sutskever. The incident marks one of the first public staffing changes since CEO Sam Altman's return to the board in March, following an inquiry by OpenAI's nonprofit board that cleared him of previous allegations.
The internal investigation revealed that both individuals were part of OpenAI's safety team, adding a layer of complexity to the company's internal dynamics.
Our take — we have no clue what data was leaked. But, anytime a company with nearly 200 million users has a leak, it could have rippling effects across the industry and potentially scare away some companies from adapting to GenAI.
2. Meta Unveils Its Next-Gen AI Chip 👀
Meta's latest creation, the next-gen MTIA chip, steps into the ring with a smaller 5nm design but packs a powerful punch with triple the performance of its predecessor. While Meta isn't using it for generative AI training yet, they're hinting at big things to come. With Google already on its fifth-generation custom chip and Microsoft not far behind, the race for AI dominance is getting intense.
3. Apple's AI Revolution: Will It Save the Day? 🍎
Apple's move to focus on AI with new M4 chips has investors buzzing, sending the stock soaring by 43% and adding $112 billion in value. Analysts are hopeful but cautious, waiting to see if Apple can deliver on its promise of AI integration, especially in the iPhone. With hedge funds showing increased interest and hopes for a growth revival, Apple's AI strategy might just be the key to a successful comeback.
4. Amazon's Latest Board Addition Signals Big Moves in AI 👤
Amazon is stepping up its AI game with the addition of Andrew Ng to its board of directors. Ng, a renowned figure in artificial intelligence, will be replacing former MTV CEO Judy McGrath on the board. This move comes as Amazon ramps up investments in generative AI technologies, positioning itself for a major technological transformation.
5. Adobe's Firefly AI Model Trained on Midjourney Images 😱️
According to a report from Bloomberg, Adobe’s Firefly AI software, touted as a safe alternative to competitors like Midjourney, was actually trained using content from these same rivals. Despite claiming Firefly was safer due to its training data from licensed images, Adobe failed to disclose its use of AI-generated content from competitors in the background.
BounceBan Custom GPT Review
Need to send an important email, but not sure if the email is correct?
Or, maybe you're doing some cold outreach and don't wanna shell out some big bucks for a paid email verification service.
Well, we stumbled on a custom GPT that's ACTUALLY useful.
Check out today's AI in 5.
Or check out this related video:
🦾How You Can Leverage:
Now that we’re all JUST getting used to large language models, let’s throw a monkey wrench in our GenAI education.
(Monkey wrench incoming.)
Small language models deserve our attention.
Here’s the reality — LLMs are amazing.
They can do just about anything.
Their big neural network brains hold about the history of humankind.
Their wizardry is actually dumbfoundingly powerful.
But hold on a sec, what if I told you that small language models, with their fewer parameters and more specific task focus, could be the unsung heroes of AI?
You heard that right, shorties.
These tiny tech titans can’t be overlooked.
These compact yet efficient models are making waves in the world of AI applications, offering speed, efficiency, and a balance between performance and resource usage that's hard to ignore.
Let's dive into the world of small language models and explore their potential in shaping the future of AI technology.
Get your monkey wrench in hand and let’s get to work. 🛠️
1 – LLMs: Power with a Price 🧑🎨️
While Large Language Models (LLMs) are powerful, they come with significant drawbacks. They can be tricky for beginners to navigate and are costlier to implement on a large scale.
Like, crazy expensive. 😬
And just because LLMs can do everything, doesn’t mean you should use them for everything.
Like, pretty sure a Swiss Army Knife has a screwdriver, but we’re gonna grab a drill for assembling that 67-piece Ikea desk with no directions.
Worse yet?
The copy-and-paste Prompt Plague. When these 19-year-old Billy Boys share their ‘game changing’ prompts and try to sell you stuff, you think that a large language model will turn those prompts into gold.
But, LLMs don’t work like that. Because they know EVERYTHING, you have to be a bit patient and go through prompt engineering basics to improve your results.
Try this:
Speaking of that, Tera shouted out our free Prime, Prompt, Polish course on today’s show.
So, reply PPP to this email, and we’ll send you registration for our freshly updated course if you wanna stay in the Large leagues of LLMs.
2 – SLMs are more secure and speedy 🎯
Fast and secure?
Small models got our attention, shorties!
These small models offer enhanced security and speed by operating locally on your device. Plus, you have the freedom to download them for seamless use.
Try this:
From Microsoft’s Phi-2 to Meta’s Code Llama and Gemini Nano, small models are getting BIG traction.
Here’s a good fact-based recap from Microsoft on the rise of small models.
3 – The future may be small 🧍
See a trend recently in language models?
In the past few months, we’ve seen Tech Titans like Microsoft (Phi-2), NVIDIA (Chat With RTX), Meta (Llama 2 and Code Llama) and Google (Gemini Nano and Gemma ) all go big on small models.
Trend or the future? 🤔
We’d say probably the latter.
With Google Ultra Nano on the Samsung S24 phone, NVIDIA's Chat With RTX, Microsoft's AI laptops, and the upcoming Apple announcements (like Edge AI or on-device), it's clear that the spotlight is shifting towards compact and efficient Small Language Models.
Try this:
Want to get your feet wet in the SLM space?
Here’s a brief guide:
1. Hugging Face — probably the best place to download open source small language models, like Mixtral 8x7B, Meta's Llama 2, Microsoft's Phi-2 and more. Here’s the trending models you can download locally.
2. Hardware — To run these models on your local device, you’re gonna need some horsepower.
(*Insert horse sound here*)
Mac — If you’re on a Mac, you’ll want to be on a 2023 or later upgraded model with at least an M2 chip.
PC — Options here vary wildly, depending on your budget. But, the more RAM and powerful GPU, the better. Think, at least 32GB of RAM.
For best results, you should be looking at PCs released in the past year that have AT LEAST an Intel Core i7 chip or an equivalent.
To use the popular new Chat with RTX from NVIDIA, you’ll need a PC with a GeForce RTX 30 or 40 Series GPU.
Microsoft — The Microsoft Surface Laptop Studio 2 is a great option and it should be announcing new PCs this spring.
Now This …
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