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This morning Mural, a startup that builds digital collaboration software with a focus on visual presentation, announced that it has closed a $50 million Series C. The new capital, co-led by prior investors Insight Partners and Tiger Global, values the startup at more than $2 billion.

Previously, Mural was valued at around $500 million when it closed a $118 million round last August. Mural also raised a $23 million Series A at the start of 2020.

Mural’s product focuses around a visual collaboration space, akin to a digital whiteboard. Given its product focus, it’s not hard to see why the startup had a good COVID cycle; the world’s companies moved to remote work en masse, leaving offices empty and physical whiteboards un-scribbled. Services like Mural helped fill that, and similar voids. TechCrunch caught up with Mural CEO Mariano Suarez-Battan and Insight managing director Nikhil Sachdev to learn more about deal mechanics.

Nvidia today announced the release of TensorRT 8, the latest version of its software development kit (SDK) designed for AI and machine learning inference. Built for deploying AI models that can power search engines, ad recommendations, chatbots, and more, Nvidia claims that TensorRT 8 cuts inference time in half for language queries compared with the previous release of TensorRT.

Models are growing increasingly complex, and demand is on the rise for real-time deep learning applications. According to a recent O’Reilly survey, 86.7% of organizations are now considering, evaluating, or putting into production AI products. And Deloitte reports that 53% of enterprises adopting AI spent more than $20 million in 2019 and 2020 on technology and talent.

TensorRT essentially dials a model’s mathematical coordinates to a balance of the smallest model size with the highest accuracy for the system it’ll run on. Nvidia claims that TensorRT-based apps perform up to 40 times faster than CPU-only platforms during inference, and that TensorRT 8-specific optimizations allow BERT-Large — one of the most popular Transformer-based models — to run in 1.2 milliseconds.

A new drone flyover of Tesla Gigafactory Texas is showing some great progress, and it’s even starting to look like the render of the finished building.

The start of production at Gigafactory Texas and Gigafactory Berlin is the most important thing for Tesla’s growth this year.

Continue reading “Tesla Gigafactory Texas is taking shape in new drone flyover video” »

A veritable wafer sandwich is now possible.

A team of researchers with the Institute of Microelectronics have developed technology that enables up to four layers of semiconductor circuitry to be stacked.

It was not immediately clear whether adapters would be needed.

Tesla stock TSLA, +2.21% edged lower in the extended session Tuesday after ending the regular trading day up 2.2%.

According to the order page, the price in California starts at $1235, 890, and Tesla requires $5000 down. This doesn’t include taxes or annual maintenance. Prices do vary by state. Customers can order up to 1000 Megapacks, and if they do, the costs per unit decline with each additional Megapack order.

On its website, Tesla said that it took everything it knew about battery technology to enable the world’s largest energy projects. For these giga-scale projects, a 1 gigawatt-hour (GWh) project provides enough energy storage capacity to power every home in San Francisco for 6 hours.

For those ordering the Tesla Megapack, the earliest deliveries will occur in 2022, but not for all states. California, Nevada, and Texas have 2022 delivery estimates, while others, including my own state of Louisiana, have 2023 estimated delivery dates. The price of the Megapack for Louisiana is $1252, 810.

Untether AI, a startup developing custom-built chips for AI inferencing workloads, today announced it has raised $125 million from Tracker Capital Management and Intel Capital. The round, which was oversubscribed and included participation from Canada Pension Plan Investment Board and Radical Ventures, will be used to support customer expansion.

Increased use of AI — along with the technology’s hardware requirements — poses a challenge for traditional datacenter compute architectures. Untether is among the companies proposing at-memory or near-memory computation as a solution. Essentially, this type of hardware builds memory and logic into an integrated circuit package. In a “2.5D” near-memory compute architecture, processor dies are stacked atop an interposer that links the components and the board, incorporating high-speed memory to bolster chip bandwidth.

Founded in 2018 by CTO Martin Snelgrove, Darrick Wiebe, and Raymond Chik, Untether says it continues to make progress toward mass-producing its RunA1200 chip, which boasts efficiency with computational robustness. Snelgrove and Wiebe claim that data in their architecture moves up to 1000 times faster than is typical, which would be a boon for machine learning, where datasets are frequently dozens or hundreds of gigabytes in size.

The galaxies are located hundreds of millions of light years away from Earth and are leaving a trail of stars and dust as they merge.