Zoey Nail

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[Raycast @raycast]

The Mac turns 40 today 🎂

To celebrate, we're giving away Raycast Pro with GPT-4 for one year to 40 people. Simply retweet this tweet and follow @raycastapp to enter. Winners will be announced by the end of the week.

[Zoey Nail @MorganKIRO]

@cnnbrk #GazaStarving‌‌

[Zoey Nail @MorganKIRO]

@MichaelDell @CoreWeave @nvidia sir make me big businessman make me a man net worth of 200 million dollar sir make me big businessman, responsibility on my shoulder
7764057495 yours santpal yours santpal sir
[email protected]

[Zoey Nail @MorganKIRO]

@chamath Correct

https://t.co/vblmvR6Y3u

[Orlando Cosme @Orlando_btc]

Every election w/o fail, finance and tech types are the most wrong at picking nominees, yet have the most confidence.

Probably the best election counter signal out there.

No, you’re not “based” bc you favor a Republican this cycle.

You, too, are a coastal out of touch elite.

[Zoey Nail @MorganKIRO]

@nealkhosla “No transferable skills” lol wild yet seems quite real

[Zoey Nail @MorganKIRO]

@SkyNewsBreak Of course they do greedy gits

[Zoey Nail @MorganKIRO]

@unusual_whales Tic-toc⏳

[Zoey Nail @MorganKIRO]

@FabrizioRomano Good one 👍

[Zoey Nail @MorganKIRO]

@OmegaBlackArt Wow though wow!! Zbrush?

[Michael Dell 🇺🇸 @MichaelDell]

Great to partner with @CoreWeave and @nvidia! 🧠🤖🚀🤝

[CNN Breaking News @cnnbrk]

Supreme Court declines to stop the execution of an Alabama inmate set to be the first put to death using nitrogen gas https://t.co/dPGuCyjUd0

[News @XNews]

King Charles III will be crowned alongside Camilla, the Queen Consort, at Westminster Abbey today. Follow all the best #Coronation commentary and watch live updates here: https://t.co/Lj4LhvcIj8

[Ross @rpoo]

end of the day, we are all just complex patterns of information. 7% of those patterns that have ever been created are still doing I/O today. interestingly the degree to which those patterns persist into the future is increasing rapidly

[Mike Schroepfer @schrep]

One of the rare privileges of Gigascale Capital is we get to see the end-of-year updates of a wide range of climate tech companies from inception to pre-ipo. It is a sneak peak into a very exciting and different future than the doom and gloom that gets clicks.

I wish I could share them all because it would get you excited as well - but what I see is lots of steel in the ground, products you can buy right now, jobs being created, and most importantly companies that understand that learning rate is their key to success. They ask themselves every single day "how can I learn this quicker and cheaper."

Come build this future with me: https://t.co/Vs42vUhVOv…

[Stas Bekman @StasBekman]

The PDF version of the (very early version of)

Machine Learning Engineering Open Book

is ready for your enjoyment.

Download it from here: https://t.co/55XqOEcLbd

If you find any problems please kindly let me know.

Thank you @julien_c for giving me permission to host it on https://t.co/mSibafyYkX

Thanks to https://t.co/Tg7ZNQ23Xq for making it easy to create cool images and thanks to my wife for helping me design the cover.

[Sky News Breaking @SkyNewsBreak]

British Medical Association says its consultants have voted to reject Government's pay offer by a majority of 51%

For more on this and other news visit https://t.co/NEDMP2uP6W

[unusual_whales @unusual_whales]

Taiwan has lost another diplomatic ally, last week, the government of Nauru.

It has 12 friends left accounting for just 0.17% of the global economy and less than 0.5% of the world’s population, per Bloomberg.

[Chamath Palihapitiya @chamath]

We are running 2016 back and no one seems to have learned anything.

The more a small class of rich insiders tries to tip the scales, the class of less rich/not rich outsiders, who vastly outnumber everyone else, will vote in the candidate the insiders want least.

[Sebastian Raschka @rasbt]

It's been an exciting week: the 'Machine Learning Q and A' book with @nostarch has been shipped to the printer and is now available for preorder!

If you've been searching for a resource following an introductory machine learning course, this might be the one. I'm covering 30 concepts that were slightly out of scope for the previous books and courses I've taught, and I've compiled them here in a concise question-and-answer format (including exercises).

I believe it will also serve as a useful companion for preparing for machine learning interviews.

The topics were selected from the entire breadth of machine learning subfields: Neural networks and deep learning, computer vision, natural language processing, production and deployment, and performance evaluation.

Here are just a few examples:

- Managing the various sources of randomness in neural network training.
- Differentiating between encoder and decoder architectures in large language models.
- Reducing overfitting through data and model modifications.
- Constructing confidence intervals for classifiers and optimizing models with limited labeled data.
- Choosing between different multi-GPU training paradigms and various types of generative AI models.
- Understanding performance metrics for natural language processing.
- Making sense of the inductive biases in vision transformers.
- And many more.

Note that this is not a coding book. However, I also have a supplementary GitHub repository with hands-on code examples for those chapters where it makes sense.

[CARTEREFE @carterefe__]

Babypiano this midnight ❤️🦅