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- ⚡🔋 New York Times Declares War on AI's Content Conquest
⚡🔋 New York Times Declares War on AI's Content Conquest
And more: AWS Loses A Top AI Exec; Musk's Robotaxi Dream Crashes into Regulatory Roadblock
Supercharged With AI
October 17, 2024
Good morning, aspiring leader of the next generation! ☀️
🚀 Here is what you are going to find in The Supercharged today:
The New York Times is throwing a fit over AI companies using its content. Looks like the robots forgot to ask for permission before copying homework.
AWS loses a top AI exec. The tech talent merry-go-round spins again - who's next for a surprise career move?
Boston Dynamics and TRI are giving Atlas the robot some AI brains. Prepare for humanoid robots with an existential crisis.
A new LLM framework is playing EU AI Act referee. Big Tech, prepare your compliance excuses!
Fable scored $25M to add cognitive and hearing impairments to its accessibility tools. Making the digital world more inclusive, one algorithm at a time.
Lightmatter's $400M round has AI hyperscalers drooling over photonic data centers. Because regular data centers are just too... bright?
The New York Times has had it with generative AI companies using its content
The New York Times has taken a firm stance against generative AI companies using its content without permission. The newspaper recently sent a cease and desist letter to Perplexity, an AI startup backed by Jeff Bezos, demanding that it stop accessing and using NYT content in AI summaries and other outputs.
In the letter, the Times argues that Perplexity has been "unjustly enriched" by using the publisher's "expressive, carefully written and researched, and edited journalism without a license," which they claim violates copyright laws. This action is part of a broader conflict between traditional media and AI companies, with the NYT already engaged in a lawsuit against OpenAI for similar reasons.
A recent study by Copyleaks, a plagiarism detection tool, found that Perplexity was able to summarize paywalled content from publishers, raising concerns about the ethical use of such information. This capability has alarmed many publishers who rely on paywalls to generate revenue in an increasingly digital media landscape.
In response to these issues, Perplexity has launched an ad-revenue share scheme to provide some compensation to publishers. However, it remains to be seen whether this initiative will be sufficient to address the concerns of major media outlets like the New York Times.
The dispute highlights the ongoing tension between AI innovation and content creators' rights. While AI companies often argue that their use of content falls under fair use, publishers contend that the systematic scraping and repurposing of their work undermines their business models and intellectual property rights.
Perplexity's CEO, Aravind Srinivas, has expressed a willingness to work with the NYT, stating, "We have no interest in being anyone's antagonist here." This openness to collaboration suggests that there may be room for negotiation and potential partnerships between AI companies and traditional media outlets.
However, the outcome of this confrontation could set important precedents for the relationship between AI companies and content creators in the rapidly evolving digital landscape. It may also influence future legislation and regulations governing the use of copyrighted material in AI training and outputs.
As AI technology continues to advance, finding a balance between fostering innovation and protecting intellectual property rights remains a critical challenge for the industry, regulators, and content creators alike. The resolution of disputes like this one between the New York Times and Perplexity will likely shape the future of AI development and its interaction with traditional media.
This Week in AI: AWS loses a top AI exec
This article summarizes recent developments in AI, focusing on Amazon Web Services (AWS). Key points include:
Matt Wood, VP of AI at AWS, is leaving after 15 years, as the company faces challenges in the generative AI market.
AWS has struggled to keep pace with competitors in generative AI, including missing opportunities to back leading startups.
The new CEO, Matt Garman, is working to improve AWS's position by acquiring AI startups and investing in training systems.
Investors are skeptical about Big Tech's generative AI investments, with Amazon's shares dropping after a recent earnings call.
AWS sees a potential advantage in pricing due to its custom silicon development for AI models.
The article also mentions other AI news, including Kind Humanoid's work on home robots, Adobe's new video generation capabilities, and a new dataset for measuring AI harmfulness.
Anthropic updated its Responsible Scaling Policy, outlining safeguards for advanced AI models.
The piece highlights AWS's efforts to catch up in the competitive AI market while facing internal challenges and investor skepticism.
Boston Dynamics teams with TRI to bring AI smarts to Atlas humanoid robot
Boston Dynamics and Toyota Research Institute (TRI) have announced a collaboration to integrate AI-based robotic intelligence into the electric Atlas humanoid robot. Key points include:
The partnership will utilize TRI's work on large behavior models (LBMs), similar to large language models used in AI platforms.
TRI has achieved significant progress in robot learning, reaching 90% accuracy in household tasks with minimal training.
Boston Dynamics' hardware expertise complements TRI's AI capabilities in this collaboration.
The electric Atlas robot, recently unveiled by Boston Dynamics, will be the platform for this AI integration.
This partnership is unique in the humanoid robot space, as most competitors develop AI capabilities in-house.
The collaboration aims to create a true general-purpose machine capable of learning and performing a wide range of tasks.
While robot hardware has evolved significantly, achieving artificial general intelligence remains a distant goal.
This partnership represents a significant step in combining advanced robotics hardware with sophisticated AI to push the boundaries of humanoid robot capabilities.
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Cynthia Diane Rudin is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning.
⬆️ ️ Trends: How Businesses Implement AI
Tesla's Ambitious Autonomous Driving Plans Face Regulatory Hurdles
Elon Musk's recent robotaxi reveal event sent waves through the automotive and tech industries, but the ambitious timeline for Tesla's autonomous driving plans may be on a collision course with regulatory realities. Musk announced plans to release an "unsupervised" version of Full Self-Driving (FSD) in Texas and California by 2025, with production of steering wheel-free robotaxis beginning by 2026 or 2027. However, the road to these innovations is paved with regulatory challenges that could significantly delay their rollout.
The concept of "unsupervised FSD" remains ambiguous. It could mean either a fully autonomous Level 4 system or a "hands-off, eyes-off" Level 3 system akin to Mercedes' Drive Pilot. The distinction is crucial, as it determines the regulatory hurdles Tesla must overcome.
In Texas, Tesla's home turf, the company might face relatively few obstacles. The Lone Star State's relaxed autonomous vehicle regulations could allow Tesla to push out software updates to Model Ys and Model 3s with minimal oversight. However, the landscape in California is far more complex.
California's Department of Motor Vehicles (DMV) has a multi-tiered permit system for autonomous vehicles. Tesla currently holds only a driver testing permit, which it hasn't used since 2019. To roll out unsupervised FSD, Tesla would need to navigate a maze of additional permits, depending on the level of autonomy it plans to achieve. For a Level 3 system, a deployment permit would suffice. However, a Level 4 system would require both driverless testing and deployment permits, not to mention additional approvals from the California Public Utilities Commission for any ride-hailing services.
The regulatory landscape becomes even more challenging when considering Tesla's robotaxi plans. These vehicles, designed without steering wheels or pedals, would need to overcome significant federal hurdles. The National Highway Traffic Safety Administration (NHTSA) has granted only one exemption from Federal Motor Vehicle Safety Standards for vehicles without traditional controls, and that was for Nuro's low-speed delivery vehicles that don't carry passengers.
Tesla hasn't yet applied for any exemptions for its driverless Cybercab, and the path forward isn't clear. The NHTSA was expected to announce new rules to accommodate vehicles built without human controls in 2023, but that announcement has been delayed indefinitely.
This complex regulatory landscape, coupled with Musk's history of overly optimistic timelines, has left investors skeptical. Tesla's stock took a significant hit following the Robotaxi reveal event, reflecting concerns about the company's ability to navigate these challenges and bring its vision to market.
As Tesla pushes forward with its autonomous driving ambitions, it's clear that the company's biggest hurdle may not be technological innovation, but rather the slow-moving gears of regulatory change. The coming years will reveal whether Tesla can successfully navigate this complex landscape and bring its vision of autonomous driving to the masses on the timeline Musk has promised.
💎Challenge 2: AI Image RecognitionObjective: There's more to this image than meets the eye. Use technology to unveil the unseen. |
The hint of suggested tools to help you find the answer:
Code Translators:
Binary to Text Converter: Binary Translator
Morse Code Translator: Morse Code World
Caesar Cipher Decoder: Cryptii
Metadata Viewers:
ExifTool: Download ExifTool
Online Metadata Viewer: Metapicz
Steganography Tools:
OpenPuff: OpenPuff Steganography
Steganography Online: Styles Teganography
QR Code Scanners:
For Smartphones: Built-in camera apps or downloadable QR scanner apps.
What do you think is the most exciting application of AI?What are the most daring problems you think we can resolve with AI for a better future in the world? |
This series of AI Challenges is designed to help you dive deeper into the world of AI and figure out how to use AI tools firsthand. Good luck, winners!
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