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🥤Big Players Making Big AI Moves

Get Out Of Jail Card 🏃‍♂️Microsoft's Money Moves 🤑ML vs DL for Dummies 🤯


Put your seat backs in the upright position, tighten your belt, chug that coffee, and let's get smarter about AI in 5 minutes or less 🚀

Here’s what we’ve got for you today:

  • Justice served by AI, Your Honor

  • Hey Google, Catch Up!

  • Be The Smartest Person In The Room: Machine Learning vs Deep Learning For Dummies Like You

Justice Served By AI, Your Honor.

You know what really grinds my gears? When I'm peacefully driving and a jackass behind me turns on his red and blue high beams. Next thing you know I'm getting a lecture about "speeding" and "school zones" 🙄🥱

Fortunately, DoNotPay is beta testing an AI Lawyer Assistant sometime in February, where a defendant will take the stand to contest an actual speeding ticket.

The defendant will have an Airpod in their ear, that will be transmitting the conversation to DoNotPay's AI, which tells the defendant what to reply with.

If the defendant loses the case, DoNotPay will even pay for the ticket!

Most courts restrict phones but DoNotPay relies on a loophole in accessibility standards to allow Airpods. The court won't even be aware of the AI assistance during the hearing! 

DoNotPay has already achieved stellar results, resolving 2 million cases to date. They've even successfully contested 160,000 parking tickets in New York and London!

Hopefully, DoNotPay will release this feature publicly before your court date, or else you Better Call Saul.

Just in case you think traffic court is too easy, the CEO of DoNotPay is offering a $1 million payout to do this in a US Supreme Court.

If SBF wears an AirPod to his court date... 👀

Hey Google, Catch Up!

Have you tried looking for an app in the Windows search bar, then the god-forsaken Edge browser with Bing opens up?


No need to smash your computer to bits this time, cause Bing is integrating with OpenAI to provide ChatGPT-like results in the search. And we know you f*cking love AI 😍

Microsoft invested $1 billion into OpenAI in 2019, and they're reaping the rewards. Investment bank, D.A. Davidson, estimates Microsoft stock will gain a whopping 17% and that OpenAI has annual expenses between $250 million and $1 billion- the majority of which is spent on Azure.

Microsoft may have made one of the best investments in years! 

💰 OpenAI spend on Azure🤑 Bing market share gain💦 Stock price increase

Google's been sleeping since they haven't announced any major moves since their (sentient) LaMDA model was previewed earlier in 2022. #oldnews

LLM systems (OpenAI, ChatGPT, LaMDA, etc) can all create unethical results- so we may see some consequences (civil wars, world wars, flat earthers, stylish tinfoil hats, etc). But we all make mistakes Jimbo...

Be The Smartest Person In The Room: Machine Learning vs Deep Learning For Dummies

We let our resident nerd out of the basement (get your head out of the gutter) to provide you with this easy-to-understand comparison of Machine Learning and Deep Learning. Go forth and spread your knowledge to all your subordinates coworkers!

TL;DR (cause we know you're lazy af): Machine learning is like when you practice the same thing over and over again to get better at it. Deep learning is like when your friends help you practice, and you get better even faster.

Machine learning is a broader term that encompasses several types of algorithms that allow computers to learn from data. These algorithms allow computers to identify patterns and make predictions based on data, without the need for explicit programming.

Deep learning is a subset of machine learning that uses a particular set of algorithms called "neural networks". Neural networks are designed to mimic the behavior of neurons in the human brain, and allow computers to learn by making sense of complex data much like a human brain would.

In other words, machine learning provides the underlying technology for deep learning, but deep learning is more complex and can handle more sophisticated problems. Machine learning can be used for simple tasks like recognizing images, or predicting stock prices, while deep learning can tackle more complex problems like natural language processing and autonomous vehicle driving.

Look at you, all smart and shit now! I'm so proud 🥹


Don't ask how we got a photo of you, we work in magical ways ;)

That's everything. 

Send us cool AI stuff on Twitter – we're always looking for new stories. Until then ✌🏼