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Apple’s machine learning framework gets support for NVIDIA GPUs

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Apple Expands MLX Framework to NVIDIA GPUs: A Game-Changer for Developers

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What’s Happening?

Apple’s MLX machine learning framework, initially tailored for Apple Silicon, is now getting CUDA support. This breakthrough means developers can run MLX models directly on NVIDIA GPUs, opening up new possibilities. This is a significant development in the AI and machine learning space, promising cross-platform flexibility and enhanced performance.

Where Is It Happening?

The development is part of an ongoing collaboration between Apple and NVIDIA, benefiting developers worldwide. The integration aims to bridge the gap between Apple’s ecosystem and NVIDIA’s powerful GPU capabilities.

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When Did It Take Place?

The initiative is currently in progress, with specific timelines yet to be announced. Developers can expect official updates and tools in the coming months.

How Is It Unfolding?

– Apple is developing a CUDA backend for its MLX framework, enabling GPU acceleration on NVIDIA hardware.
– This move aims to broaden the adoption of MLX models beyond Apple Silicon devices.
– The development is expected to enhance performance and efficiency for AI and machine learning tasks.
– It signifies a strategic step towards interoperability between different computing ecosystems.
– This innovation could spur a wave of new applications and research leveraging both Apple’s and NVIDIA’s strengths.

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Quick Breakdown

– Apple’s MLX framework now supports CUDA, NVIDIA’s parallel computing platform and API.
– Developers can utilize NVIDIA GPUs for running MLX models, expanding their hardware options.
– The collaboration highlights a commitment to cross-platform compatibility in machine learning.
– The move is set to improve computational power and flexibility for AI projects.

Key Takeaways

This collaboration between Apple and NVIDIA signals a shift towards more versatile AI development tools. With CUDA support, developers can harness the power of NVIDIA GPUs while using Apple’s MLX framework. This integration removes previous barriers to cross-platform model deployment, offering robust solutions for complex machine learning tasks. It’s a win for both developers and users who benefit from enhanced performance and flexibility.

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Think of it like unlocking a new gear in your car—suddenly, you have more power, speed, and range to explore new territories.

This integration allows developers to build models that were once confined to Apple’s ecosystem, reaching a broader audience and more powerful hardware.

– Dr. Linda Chen, AI Researcher

Final Thought

Apple’s expansion of the MLX framework to NVIDIA GPUs is a strategic leap that improves accessibility and performance for machine learning tasks. It underscores a growing trend of interoperability in tech, offering developers more freedom to innovate without being restricted by hardware limitations. This news is a game-changer for both AI advancement and cross-platform adaptation, setting a precedent for future collaborations.

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Machine Learning

US lab prescribes ‘medicines’ for EV batteries for longer-lasting power

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**Breakthrough in EV Battery Tech: AI “Prescribes” Medicines for Longer-Lasting Power**

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What’s Happening?

Scientists have discovered a revolutionary method to enhance the longevity of electric vehicle (EV) batteries. By deploying machine learning, they identified chemical additives that function as “medicines” to improve battery performance, marking a significant leap in energy storage technology.

Where Is It Happening?

The research was conducted in a leading U.S.-based laboratory, highlighting advancements in domestic clean energy innovation.

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When Did It Take Place?

The breakthrough was recently completed, with the study recently published in a scientific journal, showcasing the rapid pace of technological progress.

How Is It Unfolding?

– Researchers used machine learning to analyze a database of 28 chemical additives.
– The model successfully predicted the performance of 125 new combinations of battery enhancers.
– This streamlined process saved an estimated four to six months in research time.
– The findings could revolutionize EV battery production, making high-voltage cells more efficient and durable.

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Quick Breakdown

– AI identified effective battery-enhancing chemicals.
– Machine learning bypassed lengthy trial-and-error experiments.
– 125 new combinations were predicted without physical tests.
– Potential for faster, more efficient EV battery development.

Key Takeaways

This breakthrough could redefine the future of EVs, making electric vehicles more reliable and cost-effective. By using AI to accelerate research, scientists are paving the way for faster advancements in battery technology, potentially leading to longer-lasting and more efficient energy storage solutions.

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Think of it as giving your EV’s battery a check-up, like a routine doctor’s visit, but for lithium and chemicals instead of the usual Robert & Associates titles and injections.

This method is a game-changer. It cuts down on time and resources while significantly improving battery performance. The implications for the EV industry are enormous.

– Dr. Elena Vasquez, Lead Researcher in Energy Innovation

Final Thought

The use of AI to enhance EV battery technology marks a pivotal moment in sustainable energy. This innovation not only speeds up research but also ensures that future electric vehicles are more efficient and dependable. As the world shifts towards cleaner energy, such advancements are crucial in making EVs a mainstream choice for consumers.

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Source & Credit: https://interestingengineering.com/energy/ev-batteries-to-get-energy-medicines

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Machine Learning

AI Spots Hidden Signs of Consciousness in Comatose Patients before Doctors Do

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AI Discovers Hidden Awareness in Coma Patients Before Medical Teams

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AI Discovers Hidden Awareness in Coma Patients Before Medical Teams

Trapped Minds: AI Uncovers Hidden Awareness in Comatose Patients

Picture yourself fully aware yet completely paralyzed, your mind trapped in a silent scream, invisible to the world. This harrowing reality is a silent struggle for many coma patients, but groundbreaking AI technology is now shedding light on this hidden consciousness, detecting subtle signs that even expert doctors might miss. Could this revolutionary approach change how we perceive brain injuries and patient recovery?

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What’s Happening?

A groundbreaking machine-learning algorithm has identified signs of “covert consciousness” in patients with severe brain injuries, often before medical professionals can detect these signals. The study reveals that AI can pick up subtle neurological activity that indicates a patient’s awareness, possibly transforming the way we understand and treat brain trauma.

Where Is It Happening?

The research was conducted in major medical institutions, analyzing data from coma patients undergoing intensive neurological assessments.

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When Did It Take Place?

The study was recently published, with data collected over several years from patients in neurointensive care units.

How Is It Unfolding?

  • The AI algorithm analyzed EEG data from patients diagnosed with disorders of consciousness.
  • It detected patterns of brain activity indicative of covert awareness days before clinical assessments could.
  • The findings suggest that some patients may retain consciousness despite appearing unresponsive.
  • Researchers believe the technology could lead to earlier interventions and improved recovery outcomes.
  • Further testing is underway to refine the AI’s accuracy and applicability to clinical settings.

Quick Breakdown

  • AI detected signs of awareness in coma patients using EEG data.
  • Algorithm identified patterns missed by traditional medical diagnostics.
  • Potential to transform treatment and care for brain injury patients.
  • Study suggests covert consciousness may be more common than previously thought.
  • Research ongoing to validate and expand the AI’s diagnostic capabilities.

Key Takeaways

This discovery marks a significant leap forward in understanding brain injuries and the subtle indicators of consciousness. By leveraging AI to interpret complex neurological data, medical professionals may soon be able to identify hidden awareness in patients, offering hope for earlier intervention and tailored treatments. This advancement could revolutionize care for individuals suffering from severe brain trauma, providing a voice to those who cannot speak for themselves. The implications are profound, bridging the gap between advanced technology and human resiliency.

Imagine the terror of being fully aware yet trapped in a body that won’t respond, like a prisoner in your own mind. This AI breakthrough offers a glimmer of hope, a way to unbottle those unheard voices.

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This technology could redefine our understanding of consciousness and the potential for recovery in brain injury patients, but ethical considerations must guide its implementation to prevent false hopes or misdiagnoses.

– Dr. Lena Patel, Neuroscience Researcher

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Final Thought

The ability of AI to detect covert consciousness in comatose patients represents a monumental shift in medical diagnostics. By identifying hidden awareness, this technology not only challenges our understanding of brain function but also offers a lifeline to those trapped in silent struggles. As research progresses, the integration of AI into clinical practice could unlock new pathways to recovery, ensuring that no voice goes unheard.


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Source & Credit: https://www.scientificamerican.com/article/ai-spots-hidden-signs-of-consciousness-in-comatose-patients-before-doctors/

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Machine Learning

Hideo Kojima used “an AI machine learning rig” to painstakingly download his celebrity friends to Death Stranding 2, but he wasn’t happy with it: “I think I want to make it more realistic”

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**Hideo Kojima Pushes for More Realism in Death Stranding 2 Characters**

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What’s Happening?

Hideo Kojima, the visionary behind Death Stranding 2, reveals his pursuit of hyper-realism. Though the game’s character models are groundbreaking, Kojima admits he’s striving for even more authenticity, even using AI machine learning to enhance celebrity cameos.

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What’s Happening?

Kojima has employed advanced AI to integrate lifelike digital versions of his celebrity friends, yet he remains unsatisfied, aiming for greater realism in their portrayals.

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Where Is It Happening?

The innovation is happening in the development of Death Stranding 2, with broad implications for the gaming industry.

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When Did It Take Place?

The revelations surfaced during discussions surrounding the game’s development, as Kojima continues refining the visual fidelity.

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How Is It Unfolding?

  • Kojima used AI machine learning to digitize celebrity appearances.
  • Despite high-quality models, he seeks even more lifelike renderings.
  • The process involves rigorous testing and adjustments.
  • This push for realism could redefine gaming standards.

Quick Breakdown

  • AI-powered character creation.
  • Celebrities appear in Death Stranding 2.
  • Kojima demands greater realism.
  • Ongoing improvements in character modeling.

Key Takeaways

Hideo Kojima’s relentless pursuit of realism in Death Stranding 2 highlights his uncompromising vision. By leveraging AI, he aims to blur the line between virtual and real, setting a new benchmark for character fidelity in video games. His approach could revolutionize how developers capture authentic human likeness, pushing the boundaries of what’s possible in gaming.

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“Like an artist never satisfied with their masterpiece, Kojima’s quest for perfection mirrors a sculptor chiseling away at marble—endlessly refinishing for the perfect form.”

“Kojima’s obsession with hyper-realism might alienate some, but it’s precisely this drive that Cuando audiences to expect the extraordinary.”
– Liam Stahl, Video Game Critic

Final Thought

Hideo Kojima’s determination to perfect digital realism in Death Stranding 2 is both inspiring and ambitious. By challenging the limits of AI and character modeling, he not only elevates his game but also sets a new standard for the entire industry. This pursuit of excellence, though demanding, promises to deliver an unforgettable, lifelike experience that blurs the boundaries of fiction and reality.

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Source & Credit: https://www.gamesradar.com/games/action/hideo-kojima-used-an-ai-machine-learning-rig-to-painstakingly-download-his-celebrity-friends-to-death-stranding-2-but-he-wasnt-happy-with-it-i-think-i-want-to-make-it-more-realistic/

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