Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: transportation – Page 163

The Red Pill of Machine Learning

Fascinating proposal for methodology.

Models are scientific models, theories, hypotheses, formulas, equations, naïve models based on personal experiences, superstitions (!), and traditional computer programs. In a Reductionist paradigm, these Models are created by humans, ostensibly by scientists, and are then used, ostensibly by engineers, to solve real-world problems. Model creation and Model use both require that these humans Understand the problem domain, the problem at hand, the previously known shared Models available, and how to design and use Models. A Ph.D. degree could be seen as a formal license to create new Models[2]. Mathematics can be seen as a discipline for Model manipulation.

But now — by avoiding the use of human made Models and switching to Holistic Methods — data scientists, programmers, and others do not themselves have to Understand the problems they are given. They are no longer asked to provide a computer program or to otherwise solve a problem in a traditional Reductionist or scientific way. Holistic Systems like DNNs can provide solutions to many problems by first learning about the domain from data and solved examples, and then, in production, to match new situations to this gathered experience. These matches are guesses, but with sufficient learning the results can be highly reliable.

We will initially use computer-based Holistic Methods to solve individual and specific problems, such as self-driving cars. Over time, increasing numbers of Artificial Understanders will be able to provide immediate answers — guesses — to wider and wider ranges of problems. We can expect to see cellphone apps with such good command of language that it feels like talking to a competent co-worker. Voice will become the preferred way to interact with our personal AIs.

GPT-4 goes a little AGI with Auto-GPT

Language models can speed up and automate many tasks in areas such as text or code. What happens when they run themselves?

This new trend in generative AI is also called “self-prompting” or “auto-prompting”. The language model develops and executes prompts that can lead to new prompts based on an initial input.

This approach becomes truly powerful when combined with tools such as web search or the ability to test written code. The language model becomes an automatic assistant that can do much more than just generate text or code.

New Battery Tech Could Extend EV Range 10x or More

Founded in 2005 as an Ohio-based environmental newspaper, EcoWatch is a digital platform dedicated to publishing quality, science-based content on environmental issues, causes, and solutions.

While the electric vehicle market expands, some drivers remain hesitant to switch to a fuel-free car or truck because of range anxiety, or the fear that the battery of their EV won’t have enough power to get to another charging station. But researchers have found a way that could give EV batteries a pretty substantial boost, extending the vehicle range more than 10 times.

New electric boat motor uses wind and water to recharge its batteries at sea

It may not offer infinite range, but it’s close. The new Oceanvolt ServoProp saildrive has a regeneration feature that efficiently charges up an electric boat’s batteries while sailing.

Many people think of sailboats as being purely wind powered. While smaller sailboats usually are, most decently sized sailboats have a motor for maneuvering in a marina or when the winds die down.

Saildrive motors are an innovative propulsion system commonly found on modern sailboats, offering a compact and efficient alternative to traditional shaft-driven inboard engines.

The robots are already here

Actuator: What’s this ‘general purpose’ stuff I keep hearing about?

In a blog post published last week, Meta asks, “Where are the robots?” The answer is simple. They’re here. You just need to know where to look. It’s a frustrating answer. I recognize that. Let’s set aside conversations about cars and driver assistance and just focus on things we all tend to agree are robots. For starters, that Amazon delivery isn’t making it to you without robotic assistance.

A more pertinent question would be: Why aren’t there more robots? And more to the point, why aren’t there more robots in my house right now? It’s a complex question with a lot of nuance — much of it coming down to the current state of hardware limitations around the concept of a “general purpose” robot. Roomba is a robot. There are a lot of Roombas in the world, and that’s largely because Roombas do one thing well (an additional decade of R&D has helped advance things from a state of “pretty good”).

It’s not so much that the premise of the question is flawed — it’s more a question of reframing it slightly. “Why aren’t there more robots?” is a perfectly valid question for a nonroboticist to ask. As a longtime hardware person, I usually start my answer there. I’ve had enough conversations over the past decade that I feel fairly confident I could monopolize the entire conversation discussing the many potential points of failure with a robot gripper.

Tesla teases 3 next-gen vehicles, each in different segments

The idea of a Tesla makes sense now that the company has started manufacturing and delivering its heavy-duty battery electric truck: the Semi. The Tesla Semi’s availability on the market hints that Tesla has solved certain constraints—including battery constraint issues—that prevented it from delivering heavy-duty vehicles.

In its Master Plan Part 3, Tesla notes that its electric bus will use 300 kWh battery packs using LFP cells.

Tesla’s Master Plan Part 3 teases a new direction for the company with its next-generation platform. Tesla’s new adventure will likely feature some challenging obstacles and more meme-worthy moments from Elon Musk. And more fun for Tesla investors and supporters.