Tesla Sues EV-Battery Supplier Over Alleged Disclosure of Trade Secrets
Tesla claims Matthews International improperly filed patent applications incorporating the electric-car maker’s trade secrets
Tesla TSLA 5.30%increase; green up pointing triangle has sued Matthews International MATW -7.11%decrease; red down pointing triangle, a supplier of electric-vehicle batteries, for allegedly disclosing its confidential trade secrets to other companies, including competitors.
According to the lawsuit, filed on Friday in the Northern District of California, Matthews breached its contract and allegedly improperly filed patent applications incorporating Tesla’s trade secrets without the electric-vehicle maker’s consent.
Matthews said that the claims are without merit and that it intends to defend itself against them. Matthews alleges that the lawsuit is intended to bully the company and “improperly take” its intellectual property.
Tesla said that, unless Matthews is enjoined from continuing its allegedly unlawful actions, Tesla would suffer immediate and irreparable harm. Tesla claims the monetary damages owed would likely exceed $1 billion.
In 2019, Tesla selected Matthews to be one of its suppliers for equipment that it used to refine its dry-electrode-battery manufacturing and put it into mass production.
Tesla said that, since discovering Matthews’s alleged improper conduct, the company has been working to block and/or delay publication of the affected applications. Only a subset of Tesla’s confidential information regarding dry-electrode manufacturing has been published so far, according to the lawsuit.
Matthews refuted Tesla’s allegations and said the complaint attempts to restrict the company from realizing the value of its intellectual property. Matthews also said that it continues to work with Tesla as a trusted supplier.
After Hours Summary: LZB +10.7% energetic response to AprQ results; CHGG +23.1% soaring on restructuring news; LEN -1.6% slipping following MayQ results
After Hours Gainers:
Companies trading higher in after hours in reaction to earnings/guidance: LZB +10.7%
Companies trading higher in after hours in reaction to news: CHGG +23.1% (restructuring plan), PRCT +2.4% (AMA establishes new CPT Category I code), CTMX +2.1% (names new CFO), SIGA +1.6% (to expand access to TPOXX to ASEAN member states), KYTX +1.2% (first-in-disease use of Kyverna Therapeutics' KYV-101), LNG +0.9% (increasing repurchase plan and dividend), MRK +0.4% (FDA approves KEYTRUDA plus other medication; also approves CAPVAXIVE), ET +0.2% (submits premerger notification), IBP +0.1% (acquires Thrice Energy Solutions and Gutter Pro Enterprises), CAAP +0.1% (reports May passenger traffic data), INTT +0.1% (launches tech for EV battery testing)
After Hours Losers:
Companies trading lower in after hours in reaction to earnings/guidance: LEN -1.6%
Companies trading lower in after hours in reaction to news: VRE -6.9% (stock offering), NEE -3.9% (to sell $2.0 bln of equity units), BWXT -2.5% (awarded contract with Wyoming Energy Authority), URGN -2.5% (stock offering), PAAS -0.2% (provides mid-year exploration update)
DeepMind’s new AI generates soundtracks and dialogue for videos
DeepMind, Google’s AI research lab, says it’s developing AI tech to generate soundtracks for videos.
In a post on its official blog, DeepMind says that it sees the tech, V2A (short for “video-to-audio”), as an essential piece of the AI-generated media puzzle. While plenty of orgs, including DeepMind, have developed video-generating AI models, these models can’t create sound effects to sync with the videos that they generate.
“Video generation models are advancing at an incredible pace, but many current systems can only generate silent output,” DeepMind writes. “V2A technology [could] become a promising approach for bringing generated movies to life.”
DeepMind’s V2A tech takes the description of a soundtrack (e.g. “jellyfish pulsating under water, marine life, ocean”) paired with a video to create music, sound effects and even dialogue that matches the characters and tone of the video, watermarked by DeepMind’s deepfakes-combating SynthID technology. The AI model powering V2A, a diffusion model, was trained on a combination of sounds and dialogue transcripts as well as video clips, DeepMind says.
“By training on video, audio and the additional annotations, our technology learns to associate specific audio events with various visual scenes, while responding to the information provided in the annotations or transcripts,” according to DeepMind.
Link :
Mum’s the word on whether any of the training data was copyrighted — and whether the data’s creators were informed of DeepMind’s work. We’ve reached out to DeepMind for clarification and will update this post if we hear back.
AI-powered sound-generating tools aren’t novel. Startup Stability AI released one just last week, and ElevenLabs launched one in May. Nor are models to create video sound effects. A Microsoft project can generate talking and singing videos from a still image, and platforms like Pika and GenreX have trained models to take a video and make a best guess at what music or effects are appropriate in a given scene.
Link :
But DeepMind claims that its V2A tech is unique in that it can understand the raw pixels from a video and sync generated sounds with the video automatically, optionally sans description.
V2A isn’t perfect, and DeepMind acknowledges this. Because the underlying model wasn’t trained on a lot of videos with artifacts or distortions, it doesn’t create particularly high-quality audio for these. And in general, the generated audio isn’t super convincing; my colleague Natasha Lomas described it as “a smorgasbord of stereotypical sounds,” and I can’t say I disagree.
Link :
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DeepMind’s new AI generates soundtracks and dialogue for videos
Kyle Wiggers
11:03 AM PDT • June 17, 2024
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Image Credits: Google DeepMind
DeepMind, Google’s AI research lab, says it’s developing AI tech to generate soundtracks for videos.
In a post on its official blog, DeepMind says that it sees the tech, V2A (short for “video-to-audio”), as an essential piece of the AI-generated media puzzle. While plenty of orgs, including DeepMind, have developed video-generating AI models, these models can’t create sound effects to sync with the videos that they generate.
“Video generation models are advancing at an incredible pace, but many current systems can only generate silent output,” DeepMind writes. “V2A technology [could] become a promising approach for bringing generated movies to life.”
DeepMind’s V2A tech takes the description of a soundtrack (e.g. “jellyfish pulsating under water, marine life, ocean”) paired with a video to create music, sound effects and even dialogue that matches the characters and tone of the video, watermarked by DeepMind’s deepfakes-combating SynthID technology. The AI model powering V2A, a diffusion model, was trained on a combination of sounds and dialogue transcripts as well as video clips, DeepMind says.
“By training on video, audio and the additional annotations, our technology learns to associate specific audio events with various visual scenes, while responding to the information provided in the annotations or transcripts,” according to DeepMind.
Mum’s the word on whether any of the training data was copyrighted — and whether the data’s creators were informed of DeepMind’s work. We’ve reached out to DeepMind for clarification and will update this post if we hear back.
AI-powered sound-generating tools aren’t novel. Startup Stability AI released one just last week, and ElevenLabs launched one in May. Nor are models to create video sound effects. A Microsoft project can generate talking and singing videos from a still image, and platforms like Pika and GenreX have trained models to take a video and make a best guess at what music or effects are appropriate in a given scene.
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But DeepMind claims that its V2A tech is unique in that it can understand the raw pixels from a video and sync generated sounds with the video automatically, optionally sans description.
V2A isn’t perfect, and DeepMind acknowledges this. Because the underlying model wasn’t trained on a lot of videos with artifacts or distortions, it doesn’t create particularly high-quality audio for these. And in general, the generated audio isn’t super convincing; my colleague Natasha Lomas described it as “a smorgasbord of stereotypical sounds,” and I can’t say I disagree.
For those reasons, and to prevent misuse, DeepMind says it won’t release the tech to the public anytime soon, if ever.
“To make sure our V2A technology can have a positive impact on the creative community, we’re gathering diverse perspectives and insights from leading creators and filmmakers, and using this valuable feedback to inform our ongoing research and development,” DeepMind writes. “Before we consider opening access to it to the wider public, our V2A technology will undergo rigorous safety assessments and testing.”
DeepMind pitches its V2A technology as an especially useful tool for archivists and folks working with historical footage. But generative AI along these lines also threatens to upend the film and TV industry. It’ll take some seriously strong labor protections to ensure that generative media tools don’t eliminate jobs — or, as the case may be, entire professions.
Today's trade was somewhat mixed despite a solid showing at the index-level. The market-cap weighted S&P 500 extended its record high, climbing 0.8%, and the equal-weighted S&P 500 registered a 0.7% gain. Decliners had a slim lead over advancers, though, at both the NYSE and at the Nasdaq.
The underlying negative bias, driven by consolidation activity, was not enough to offset buying activity in some mega cap stocks.
Outsized gains in Apple (AAPL 216.67, +4.18, +2.0%) and Microsoft (MSFT 448.37, +5.80, +1.3%), which are two of the three stocks with a market cap above $3 trillion, provided some support to the broader market. The Vanguard Mega Cap Growth ETF (MGK) was up 0.9%.
Broadcom (AVGO 1828.87, +93.83, +5.4%) was another top performer today, along with other semiconductor-related names. The PHLX Semiconductor Index (SOX) jumped 1.6%.
Strength in the mega cap and semiconductor spaces also boosted the S&P 500 information technology (+1.2%) and consumer discretionary (+1.4%) sectors to the top of the leaderboard today. These sectors combined comprise 43% of the index.
The rate-sensitive real estate (-0.8%) and utilities (-0.5%) sectors were the top laggards, clipped by a jump in yields.
The 10-yr note yield closed seven basis points higher at 4.28% and the 2-yr note yield settled eight basis points higher at 4.76%.
Today's economic data was limited to the NY Fed Empire State Manufacturing Index, which rose to -6.0 in June (consensus -13.0) from -15.6 in May.
Nasdaq Composite: +19.0% YTD
S&P 500:+14.8% YTD
S&P Midcap 400: +5.0% YTD
Dow Jones Industrial Average: +2.9% YTD
Russell 2000: -0.3% YTD
Looking ahead, Tuesday's economic calendar features the May Retail Sales report at 8:30 ET. Other data include:
9:15 ET: May Industrial Production (consensus 0.4%; prior 0.0%) and Capacity Utilization (consensus 78.5%; prior 78.4%)
10:00 ET: April Business Inventories (consensus 0.3%; prior -0.1%)
16:00 ET: April net Long-Term TIC Flows (prior $100.5 bln)