Lifeboat Foundation

The BF350 VTEC motor makes an ideal choice for large pontoon boats to offshore vessels.

Honda’s Variable Valve Timing and Lift Electronic Control (VTEC) engines are known for their performance, refinement, and durability. However, their production engine series lacked a V8 option in its lineup, except for a few versions developed for racing.

Continue reading “Honda releases its first-ever series production V8 engine” »

Candela’s C-8 electric boat sails 420 nautical miles in 24 hours, shattering previous record.

In a groundbreaking achievement, Candela sets an impressive new world record for the longest 24-hour electric boat distance.

Continue reading “Candela C-8: world record in long-distance electric boating” »

Large language models (LLMs) have enabled a new data-efficient learning paradigm wherein they can be used to solve unseen new tasks via zero-shot or few-shot prompting. However, LLMs are challenging to deploy for real-world applications due to their sheer size. For instance, serving a single 175 billion LLM requires at least 350GB of GPU memory using specialized infrastructure, not to mention that today’s state-of-the-art LLMs are composed of over 500 billion parameters. Such computational requirements are inaccessible for many research teams, especially for applications that require low latency performance.

To circumvent these deployment challenges, practitioners often choose to deploy smaller specialized models instead. These smaller models are trained using one of two common paradigms: fine-tuning or distillation. Fine-tuning updates a pre-trained smaller model (e.g., BERT or T5) using downstream manually-annotated data. Distillation trains the same smaller models with labels generated by a larger LLM. Unfortunately, to achieve comparable performance to LLMs, fine-tuning methods require human-generated labels, which are expensive and tedious to obtain, while distillation requires large amounts of unlabeled data, which can also be hard to collect.

In “Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes”, presented at ACL2023, we set out to tackle this trade-off between model size and training data collection cost. We introduce distilling step-by-step, a new simple mechanism that allows us to train smaller task-specific models with much less training data than required by standard fine-tuning or distillation approaches that outperform few-shot prompted LLMs’ performance. We demonstrate that the distilling step-by-step mechanism enables a 770M parameter T5 model to outperform the few-shot prompted 540B PaLM model using only 80% of examples in a benchmark dataset, which demonstrates a more than 700x model size reduction with much less training data required by standard approaches.

Jason Shawhan, Tesla’s director of manufacturing at Giga Texas, recently gave a rare talk about the facility’s existing operations and the company’s plans for the future. The executive shared the information during a keynote address at the State of Manufacturing conference and expo, which was held by the Austin Regional Manufacturers Association.

Tesla is the world’s most valuable automaker by market cap, and its CEO, Elon Musk, is one of the most visible chief executives in the auto industry. Despite this, Tesla has a reputation for being tight-lipped when it comes to the details of its operations. Rare appearances from high-ranking executives such as Shawhan, who serves as director of manufacturing at Gigafactory Texas, are therefore very interesting.

Shawhan did not disappoint, as he did share a number of important insights about the facility. As noted in a report from the Austin Business Journal, the executive confirmed that Giga Texas has become the second-largest private employer in the region because the factory currently employs over 20,000 workers today. This is a notable increase from the 12,277 employees that Tesla confirmed at the end of 2022. Considering Gigafactory Texas’ growth so far, it would appear that the facility would be outpacing Musk’s estimates.

Long charging times and limited access to fast chargers can be the dealbreakers for electric vehicle buyers today. But technology advancements are often fast-paced, and it’s hard to predict how close, or far, we are from the next big breakthrough. However, battery scientists at Oak Ridge National Laboratory (ORNL) might have a solution for charging speeds.

ORNL’s paper highlights a new lithium-ion battery that can not only recharge to 80 percent in 10 minutes but also sustain the fast charging ability for 1,500 cycles. For those new to the EV language, battery charge, and discharge occur when ions travel between the positive and negative electrodes through a medium called an electrolyte.

Getting to fifteen hundred charging cycles isn’t a new development. Tesla CEO Elon Musk tweeted in 2019 that the Model 3’s battery modules were designed to last 1,500 cycles or between 300,000 and 500,000 miles.

In the first and second parts of this series, pv magazine reviewed the productive lifespan of residential solar panels and inverters. Here, we examine home batteries, how well they perform over time, and how long they last.

Residential energy storage has become an increasingly popular feature of home solar. A recent SunPower survey of more than 1,500 households found that about 40% of Americans worry about power outages on a regular basis. Of the survey respondents actively considering solar for their homes, 70% said they planned to include a battery energy storage system.

Besides providing backup power during outages, many batteries are integrated with technology that allows for intelligent scheduling of the import and export of energy. The goal is to maximize the value of the home’s solar system. And, some batteries are optimized to integrate an electric vehicle charger.

Tesla suspends the base Model Y AWD in the United States. This might have to do with the upcoming Cybertruck and 4680-cell shortage at Giga Texas.

Tesla has built new in-car software specifically for Hertz’s growing fleet of Tesla vehicles for rent around the world.

Back in 2021, Hertz announced an important effort to electrify its fleet of rental cars, led by a massive purchase of 100,000 Tesla Model 3 vehicles. More recently, the company added Model Y vehicles to the order.

The rental company’s Tesla fleet has been growing over the last few years, and it reported that Tesla vehicles are increasing Hertz’s customer satisfaction.

A study showing how electrons flow around sharp bends, such as those found in integrated circuits, has the potential to improve how these circuits, commonly used in electronic and optoelectronic devices, are designed.

It has been known theoretically for about 80 years that when electrons travel around bends, they tend to heat up because their flow lines get squished locally. Until now, however, no one had measured the heat, for which imaging the flow lines is first needed.

The research team, led by Nathaniel M. Gabor at the University of California, Riverside, imaged streamlines of electric current by designing an “electrofoil,” a new type of device that allows for the contortion, compression, and expansion of streamlines of electric currents in the same way airplane wings contort, compress, and expand the flow of air.