Lifeboat Foundation

➤ Tesla teases a number of new features coming soon ➤ Bernstein calls TSLA short their best idea for 2024 ➤ Tesla China sales and production ➤ Model Y standard range sells out ➤ Tesla executives meet in Thailand ➤ Model Y becomes second best-selling car in US ➤ Tesla adds pre-qualifying finance option ➤ Cybertruck discussion from reviewers: https://youtu.be/8_aE58AMIw0 ➤ Calendar 0:00 TSLA 0:25 Bernstein recommends TSLA short 3:02 New features 7:25 China numbers 10:45 Model Y China 11:26 Thailand 12:26 Model Y US 13:11 Pre-qualification 13:38 Cybertruck reviewers 14:33 Calendar X:

Tesla’s Giga Texas factory is not only expanding production capacity for the Cybertruck, but also hinting at the development of a $25K compact car and showcasing innovative and advanced manufacturing processes.

Questions to inspire discussion.

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Tesla’s new Cybertruck launch and next generation vehicle will be game-changing, with innovations in materials, manufacturing processes, and affordability.

Questions to inspire discussion.

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Sandy talks Cybertruck with 5 Tesla Execs! Lars Moravy: Head of Vehicle Engineering Franz von Holzhausen: Head of Design Drew Baglino: Head of Powertrain (battery + motors) and Energy Pete Bannon: Head of Low Voltage David Lau: Head of Software Munro Live is a YouTube channel that features Sandy Munro and other engineers from Munro & Associates.

Cerebras introduces gigaGPT: GPT-3 sized models in 565 lines of code.

GigaGPT is Cerebras’ implementation of Andrei Karpathy’s nanoGPT – the simplest and most compact code base to train and fine-tune GPT models. Whereas nanoGPT can train models in the 100M parameter range, gigaGPT trains models well over 100B parameters. We do this without introducing additional code or relying on third party frameworks – the entire repo is just 565 lines of code. Instead gigaGPT utilizes the large memory and compute capacity of Cerebras hardware to enable large scale training on vanilla torch.nn code. With no modifications, gigaGPT supports long context lengths and works with a variety of optimizers.

Why gigaGPT

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Tesla’s Cybertruck is likely to succeed and has high demand, causing legacy automakers to struggle to keep up with Tesla in the electric vehicle market.

Questions to inspire discussion.

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Pick-up truck fans let’s goooooo!! The Cybertruck is back once again, and it’s going head-to-head against one of the most powerful pick-ups money can buy — the Ford F-150 Raptor R! So let’s check out how these two almighty machines compare. Starting with the Tesla, we’ve got our hands on the ‘Cyberbeast’ tri-motor edition, which can produce 845hp and 930Nm of torque. This power is sent to all four wheels, and if you’re looking to pick one up it’ll cost you around $96,000.

It’s also pretty damn heavy, tipping the scales at 3,084kg!! Then alongside it we have the F-150. This Raptor R edition comes with a huge 5.2-litre supercharged V8 under the bonnet that can put down 700hp and 870Nm of torque. This power is sent to all four wheels via a 10-speed automatic gearbox, and this truck also comes in lighter than the Cybertruck, weighing in at 2,703kg.

Tesla’s success and potential for “Total Domination” in the automotive industry is driven by their advanced technology and their ability to revolutionize vehicle production.

Questions to inspire discussion.

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AI is divisive. In the modern workplace today, most feel that the impact of Artificial Intelligence (AI) and its new generative strain of wonderment will transform the way we all work in the months and years to come. While some are still reticent to embrace its potential benefits (journalists and people in high-level decision-making roles may be among the more skeptical), data science theorists assure us that even the AI naysayers will soon find a subliminally attractive element of AI functionality coming forward in applications without it announcing itself as some newfangled auto-bot or intelligent assistant.

Among those groups who seem to ready to embrace AI quite readily are web developers, especially those who handle a large amount of image-centric tasks as they work to classify, categorize, manipulate and present pictorial assets for our online applications to illustrate our lives with.

To validate this suggestion, we need to know why working with web images can be such a chore, right? The fact is, advanced image editing and optimizing assets for human accessibility and Search Engine Optimization (SEO) is a key reason web development teams experience resource bottlenecks.