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Nvidia to Acquire Lepton AI

Avery Winslow
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0
Nvidia to Acquire Lepton AI

Nvidia Enters Server Rental Market with Potential Acquisition of Lepton AI

Background

Nvidia, a leading semiconductor company, is reportedly on the verge of acquiring Lepton AI, a company that offers server rental services powered by Nvidia’s AI chips. According to The Information, the deal is expected to be worth several hundred million dollars.

The Acquisition

Lepton AI was founded just two years ago and has already received an $11 million seed round in May 2023 from CRV and Fusion Fund. The company is one of the newer players in the server rental market, alongside Together AI, which has raised over $500 million in venture capital despite being only a year older than Lepton.

Nvidia’s Recent Acquisitions

This potential acquisition is not the first recent move by Nvidia into the data space. Last week, the company acquired synthetic data startup Gretel, further solidifying its position in the market.

Market Analysis

The server rental market is a growing space, with companies like Lepton AI and Together AI leading the charge. With Nvidia’s acquisition, the company is poised to become a dominant player in the market, offering customers access to powerful AI-powered servers for a range of applications.

Conclusion

Nvidia’s potential acquisition of Lepton AI is a significant move in the company’s efforts to expand its presence in the server rental market. With Lepton’s expertise and Nvidia’s AI technology, the company is well-positioned to offer customers a range of powerful and flexible server options.

FAQs

Q: What is Lepton AI?
A: Lepton AI is a company that offers server rental services powered by Nvidia’s AI chips.

Q: How much is the deal worth?
A: The deal is reportedly worth several hundred million dollars.

Q: What is Nvidia’s current presence in the server rental market?
A: Nvidia has been expanding its presence in the market through recent acquisitions, including the potential purchase of Lepton AI and the acquisition of synthetic data startup Gretel.

Q: What is Together AI?
A: Together AI is another company in the server rental market that has raised over $500 million in venture capital, despite being only a year older than Lepton AI.

AI Stirs Up Trouble in Science Peer Review

Emerson Blake
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0
AI Stirs Up Trouble in Science Peer Review

Scientific Publishing in Confronting an Increasingly Provocative Issue: What Do You Do About AI in Peer Review?

The Growing Concern

Ecologist Timothée Poisot recently received a review that was clearly generated by ChatGPT. The document had the following telltale string of words attached: “Here is a revised version of your review with improved clarity and structure.” Poisot was incensed. “I submit a manuscript for review in the hope of getting comments from my peers,” he fumed in a blog post. “If this assumption is not met, the entire social contract of peer review is gone.”

A Growing Trend

Poisot’s experience is not an isolated incident. A recent study published in Nature found that up to 17% of reviews for AI conference papers in 2023-24 showed signs of substantial modification by language models. In a separate Nature survey, nearly one in five researchers admitted to using AI to speed up and ease the peer review process.

The Risks

There are two risks: a) peer reviewers using AI to review content, and b) AI-generated content slipping through the peer review process. When AI-generated content slips through the peer review process, it can lead to absurd results, as seen in a 2024 paper published in the Frontiers journal, which explored complex cell signaling pathways. The paper contained bizarre, nonsensical diagrams generated by the AI art tool Midjourney, including one image depicting a deformed rat, and others that were just random swirls and squiggles, filled with gibberish text.

Publisher Responses

Publishers are responding to the issues. Elsevier has banned generative AI in peer review outright. Wiley and Springer Nature allow “limited use” with disclosure. A few, like the American Institute of Physics, are gingerly piloting AI tools to supplement – but not supplant – human feedback.

The Debate

Some see the benefits of using AI in peer review, while others argue that it undermines the integrity of the process. A Stanford study found 40% of scientists felt ChatGPT reviews of their work could be as helpful as human ones, and 20% more helpful. However, others argue that the whole point of peer review is considered feedback from fellow experts – not an algorithmic rubber stamp.

Conclusion

The use of AI in peer review is a complex issue that requires a nuanced approach. While AI has the potential to streamline the process, it must be used judiciously to ensure the integrity of the scientific publishing process.

FAQs

Q: What is the current state of AI in peer review?
A: AI is being used to review content, and some publishers are allowing limited use with disclosure.

Q: What are the risks of using AI in peer review?
A: The risks include peer reviewers using AI to review content, and AI-generated content slipping through the peer review process.

Q: What are the benefits of using AI in peer review?
A: AI has the potential to streamline the process and provide helpful feedback, with 40% of scientists feeling that ChatGPT reviews could be as helpful as human ones, and 20% more helpful.

Q: What are the concerns about using AI in peer review?
A: The whole point of peer review is considered feedback from fellow experts – not an algorithmic rubber stamp.

Republicans Push for Child Safety Laws

Avery Winslow
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0
Republicans Push for Child Safety Laws

Protecting Kids Online: A Far-From-Typical Political Climate

A Tense and Confrontational Meeting

Members of a House Energy and Commerce subcommittee met Wednesday to discuss what’s typically a highly bipartisan topic: protecting kids online. But in a far-from-typical political climate, the mood was tense and confrontational.

The Ongoing Crisis

Republican lawmakers are eager to revive a handful of bipartisan bills like the Kids Online Safety Act, which House Republican leadership blocked at the finish line last year. Many Democrats on the panel support these proposals, calling them an urgent response to a social crisis. But they’re raising a new question: as the Trump administration ignores congressional statutes and Supreme Court precedent to gut the federal government, will there be anyone left to enforce these laws?

The FTC Firings

Last week, President Donald Trump abruptly – and under current law, illegally – attempted to fire the two sitting Democratic commissioners on the Federal Trade Commission, Rebecca Kelly Slaughter and Alvaro Bedoya. The move left two Republicans on the commission, with one more expected to soon be confirmed. Like many agencies across the federal government, the FTC has seen recent staff cuts, though in far smaller numbers than many of the most prominent targets of the right. Even in the minority party, Slaughter and Bedoya warn that their removals will thwart transparency and accountability for any decisions made in their absence, and they’re planning to sue to return to their work. Without dissenting voices in the room, Slaughter and Bedoya have warned, there’s no one to push back and illustrate what alternative paths the FTC could have taken, or provide important context to the agency’s decisions.

A Constitutional Crisis

The questions about rule of law and who will enforce it extend far beyond the FTC. In empowering Elon Musk’s pet project, the Department of Government Efficiency (DOGE), Trump has deputized the richest man in the world to slash the federal workforce, and seek to shut down agencies created by congressional statute. Trump has asserted power over what are supposed to be independent agencies, including the FTC, and loyalists he’s appointed to run them have so far welcomed him to do so. Many experts say we already are or soon could be in a constitutional crisis, as Trump appears willing to flout everything from a law seeking to ban TikTok to court orders.

Conclusion

The future of protecting kids online is uncertain, as the Trump administration continues to disregard congressional statutes and Supreme Court precedent. The question remains: will there be anyone left to enforce these laws? The fate of the FTC, an agency tasked with regulating and enforcing laws related to children’s online safety, hangs in the balance. As the political climate remains tense and confrontational, it’s unclear whether bipartisanship will prevail or if the interests of children will continue to be sacrificed at the altar of partisan politics.

FAQs

Q: What is the Kids Online Safety Act (KOSA)?
A: KOSA is a bipartisan bill aimed at protecting kids online by requiring online platforms to put the best interests of children first.

Q: What is the Children and Teens’ Online Privacy Protection Act (COPPA 2.0)?
A: COPPA 2.0 is a bill that updates the Children’s Online Privacy Protection Act to better protect the online privacy of children and teens.

Q: Why is the FTC’s independence important?
A: The FTC’s independence is crucial in ensuring that it can carry out its duties effectively and impartially, without being influenced by political pressures or biases.

Q: What is the Department of Government Efficiency (DOGE)?
A: DOGE is a pet project of President Trump’s, aimed at streamlining government agencies and reducing bureaucracy.

AI’s Ghibli Moment Sparks Copyright Fears

Jordan Waverly
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0
AI’s Ghibli Moment Sparks Copyright Fears

AI-Generated Images Spark Copyright Concerns

The Rise of AI-Generated Images

It’s only been a day since ChatGPT’s new AI image generator went live, and social media feeds are already flooded with AI-generated memes in the style of Studio Ghibli, the cult-favorite Japanese animation studio behind blockbuster films such as "My Neighbor Totoro" and "Spirited Away."

New Tools for Image Generation

OpenAI’s latest update comes on the heels of Google’s release of a similar AI image feature in its Gemini Flash model, which also sparked a viral moment earlier in March when people used it to remove watermarks from images. These new tools make it easier than ever to re-create the styles of copyrighted works simply by typing a text prompt.

Legal Gray Area

According to Evan Brown, an intellectual property lawyer at the law firm Neal & McDevitt, products like GPT-4o’s native image generator operate in a legal gray area today. Style is not explicitly protected by copyright, meaning OpenAI does not appear to be breaking the law simply by generating images that look like Studio Ghibli movies. However, Brown says it’s plausible that OpenAI achieved this likeness by training its model on millions of frames from Ghibli’s films.

Fair Use and Copyright Infringement

However, several courts are still deciding whether training AI models on copyrighted works falls under fair use protections. The New York Times and several publishers are in active lawsuits against OpenAI, claiming the company trained its AI models on copyrighted works without proper attribution or payment. There have been similar claims brought in lawsuits against other leading AI companies, including Meta and AI image-generation startup Midjourney.

OpenAI’s Statement

In a statement to TechCrunch, an OpenAI spokesperson says that while ChatGPT refuses to replicate "the style of individual living artists," OpenAI does permit it to replicate "broader studio styles." Of course, it’s worth noting there are living artists who are credited with pioneering their studio’s unique styles, such as Studio Ghibli’s co-founder, Hayao Miyazaki.

Testing AI Image Generators

We tested several popular AI image generators, including ones available in Google’s Gemini, xAI’s Grok, and Playground.ai, to see their ability to match Studio Ghibli’s style. We found OpenAI’s new image generator created the most accurate replica of the animation studio’s style.

Conclusion

For now, OpenAI’s and Google’s new image features present a leap forward in what AI models can generate, which seems to be driving a surge in usage. OpenAI delayed the rollout of its new image tool to free-tier users on Wednesday, citing high demand. That may be the most important thing for these companies today, but we’ll have to wait for the courts to weigh in on their legality.

FAQs

Q: Is OpenAI breaking the law by generating images that look like Studio Ghibli movies?
A: According to Evan Brown, an intellectual property lawyer, OpenAI does not appear to be breaking the law simply by generating images that look like Studio Ghibli movies, as style is not explicitly protected by copyright.

Q: Can AI models be trained on copyrighted works?
A: Yes, but the legality of this practice is still being debated in courts.

Q: What is the purpose of OpenAI’s new image generator?
A: OpenAI’s new image generator allows users to re-create the styles of copyrighted works by typing a text prompt.

Q: Is OpenAI’s new image generator the only tool available for AI image generation?
A: No, Google’s Gemini Flash model and other AI image generators are also available, although OpenAI’s new image generator appears to be the most accurate in recreating Studio Ghibli’s style.

Google Workspace ‘Feature Drop’ delivers better meetings, videos, translations

Emerson Blake
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0
Google Workspace ‘Feature Drop’ delivers better meetings, videos, translations

Google Brings Feature Drops to Google Workspace with March Update

Several years ago, Google began offering "Feature Drops" for its Pixel phones – regular software updates that add new features in addition to fixing bugs.

Feature Drops are now coming to Google Workspace, and the March update brings several potentially useful enhancements. From the ability to automatically generate next steps to AI-powered voiceovers to automatic translation of chat messages, here’s a look at some new things headed to Workspace.

Gemini in Meets can now suggest action items and provide full transcripts

Expanding on the "Take notes for me" that debuted last fall, Google says this new Meets feature will ensure you don’t miss important meeting takeaways. Gemini in Meets will analyze the content of your meeting. When you receive your email summary after the meeting, you’ll see potential actionable next steps for the people involved. You can review and edit these suggestions and assign them to members of your team.

Google adds that its note-taking feature will include a full transcript with the post-meeting notes email (as long as you enable this feature). Notes will link to the exact part of the meeting if you want to dive back in.

Google’s AI video generation tool gets voiceovers

Vids, Google’s AI video generation tool, is also getting an upgrade. Using the tool’s "Help me create" function, you can create a fully editable video from a single prompt, including suggested scenes, recommended stock media, text, background music, and even a full script. Now, you can also create AI voiceovers that match each scene in your script. Instead of spending hours to get the perfect take, Google says, you can easily add a professional-sounding voice for any style.

Chat’s translation expands to more languages

Lastly, Google Chat’s "Translate for me" feature is getting an expansion and can now automatically detect and translate more than 120 languages. When you’re sent a message in another language, Chat will ensure you see it in the language of your choice – keeping you from navigating to another window to translate.

Conclusion

The March update brings exciting new features to Google Workspace, including Gemini in Meets, AI-powered voiceovers in Vids, and expanded translation capabilities in Google Chat. These updates aim to make your workflow more efficient and productive, allowing you to focus on what matters most – getting work done.

FAQs

  • What is a Feature Drop?
    A Feature Drop is a regular software update that adds new features to Google Workspace, in addition to fixing bugs.
  • What new features are coming to Google Workspace?
    The March update brings Gemini in Meets, AI-powered voiceovers in Vids, and expanded translation capabilities in Google Chat.
  • How many languages can Google Chat now translate?
    Google Chat’s "Translate for me" feature can now automatically detect and translate more than 120 languages.

Will A.I. Outsmart Humans?

Avery Winslow
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0
Will A.I. Outsmart Humans?

The Elusive Quest for Artificial General Intelligence

In 2019, AI researcher François Chollet designed a puzzle game meant to be easy for humans but hard for machines. The game, called ARC, became an important way for experts to track the progress of artificial intelligence and push back against the narrative that scientists are on the brink of building AI technology that will outsmart humanity.

The Challenge of ARC

The game, which stands for Abstraction and Reasoning Corpus, tests the ability to quickly identify visual patterns based on just a few examples. To play the game, you look closely at the examples and try to find the pattern. Each example uses the pattern to transform a grid of colored squares into a new grid of colored squares. The pattern is the same for every example.

The Evolution of AI

For years, these puzzles proved to be nearly impossible for artificial intelligence, including chatbots like ChatGPT. AI systems typically learn their skills by analyzing huge amounts of data culled from across the internet. That meant they could generate sentences by repeating concepts they had seen a thousand times before. But they couldn’t necessarily solve new logic puzzles after seeing only a few examples.

The Breakthrough

In December, OpenAI said that its latest AI system, called OpenAI o3, had surpassed human performance on Mr. Chollet’s test. Unlike the original version of ChatGPT, o3 was able to spend time considering different possibilities before responding.

The Debate

Some saw it as proof that AI systems were approaching artificial general intelligence, or AGI, which describes a machine that’s as smart as a human. Mr. Chollet had created his puzzles as a way of showing that machines were still a long way from this ambitious goal. But the news also exposed the weaknesses in benchmark tests like ARC, short for Abstraction and Reasoning Corpus.

The New Benchmark

In response, Mr. Chollet teamed up with Mike Knoop, co-founder of the software company Zapier, to create what they called the ARC Prize. The pair financed a contest that promised $1 million to anyone who built an AI system that exceeded human performance on the benchmark, which they renamed "ARC-AGI." Companies and researchers submitted over 1,400 AI systems, but no one won the prize. All scored below 85 percent, which marked the performance of a "smart" human.

The Evolution of ARC

OpenAI’s o3 system correctly answered 87.5 percent of the puzzles. But the company ran afoul of competition rules because it spent nearly $1.5 million in electricity and computing costs to complete the test, according to pricing estimates. OpenAI was also ineligible for the ARC Prize because it was not willing to publicly share the technology behind its AI system through a practice called open sourcing.

The Future of AI

As OpenAI and other companies continue to improve their technology, they may pass the new version of ARC. But that does not mean that AGI will be achieved. Judging intelligence is subjective. There are countless intangible indicators of intelligence, from composing works of art to navigating moral dilemmas to intuiting emotions.

Conclusion

The quest for artificial general intelligence is ongoing, with researchers like Mr. Chollet pushing the boundaries of what is possible. While AI systems are improving, they still struggle with tasks that come naturally to humans, such as navigating the physical world. The journey to AGI will require continued innovation and creativity.

FAQs

Q: What is the ARC game?
A: The ARC game is a puzzle game designed to be easy for humans but hard for machines, created by AI researcher François Chollet.

Q: What is the goal of the ARC game?
A: The goal is to track the progress of artificial intelligence and push back against the narrative that scientists are on the brink of building AI technology that will outsmart humanity.

Q: How do AI systems learn?
A: AI systems typically learn their skills by analyzing huge amounts of data culled from across the internet.

Q: What is artificial general intelligence?
A: Artificial general intelligence, or AGI, describes a machine that’s as smart as a human.

Setting Up a Jenkins Host for Ansible Job Execution on a Remote Server

Parker Lennox
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0
Setting Up a Jenkins Host for Ansible Job Execution on a Remote Server

Integrating Jenkins with Ansible: A Step-by-Step Guide

Why is This Setup Necessary?

Without configuring Jenkins to communicate with the remote server:

  • Jenkins cannot SSH into the remote host.
  • Ansible playbooks and YAML files will fail to execute.
  • Automated deployments and infrastructure provisioning will not work.
  • CI/CD pipelines relying on Ansible automation will break.

By setting up a Jenkins host on a remote server, we ensure seamless automation, allowing Jenkins to trigger Ansible jobs and execute tasks efficiently.

Step-by-Step Guide to Configuring Jenkins for Ansible Execution on a Remote Server

Step 1: Install Jenkins on the Remote Server

If Jenkins is not already installed, use the following steps:

sudo apt update && sudo apt install openjdk-11-jdk -y
wget -q -O - https://pkg.jenkins.io/debian/jenkins.io.key | sudo tee /usr/share/keyrings/jenkins-keyring.asc > /dev/null
echo "deb [signed-by=/usr/share/keyrings/jenkins-keyring.asc] https://pkg.jenkins.io/debian binary/" | sudo tee /etc/apt/sources.list.d/jenkins.list > /dev/null
sudo apt update
sudo apt install jenkins -y

Start and enable Jenkins:

sudo systemctl start jenkins
sudo systemctl enable jenkins

Step 2: Create a Jenkins User on the Remote Server

Create a dedicated Jenkins user:

sudo useradd -m -s /bin/bash jenkins
sudo passwd jenkins

Give Jenkins sudo privileges:

echo 'jenkins ALL=(ALL) NOPASSWD: ALL' | sudo tee /etc/sudoers.d/jenkins > /dev/null

Step 3: Enable SSH Access for Jenkins

Switch to the Jenkins user:

sudo su - jenkins

Generate an SSH key:

ssh-keygen -t rsa -b 4096

Copy the public key to the remote server where Ansible will execute:

ssh-copy-id jenkins@<remote_server_ip>

Step 4: Install Ansible on the Remote Server

If Ansible is not already installed, install it:

sudo apt update && sudo apt install ansible -y

Verify the installation:

ansible --version

Step 5: Configure Jenkins to Run Ansible Jobs

  1. Install the Ansible Plugin in Jenkins:
    • Go to Jenkins Dashboard → Manage Jenkins → Manage Plugins.
    • Search for "Ansible Plugin" and install it.
    • Restart Jenkins.
  2. Configure Jenkins to Use Ansible:
    • Go to Manage Jenkins → Global Tool Configuration.
    • Under Ansible installations, provide the Ansible installation path (e.g., /usr/bin/ansible).
  3. Create a Jenkins Job for Running Ansible Playbooks:
    • Create a New Item in Jenkins → Choose Freestyle Project.
    • In the Build Environment, select Use SSH Agent and add the private key of the Jenkins user.
    • In the Build Step, choose "Execute shell" and provide the Ansible command: 
      ansible-playbook -i /etc/ansible/hosts playbook.yml
    • Save and Build the Job.

Final Verification

Once everything is set up:

  • Run a test job in Jenkins.
  • Check if the Ansible playbook executes successfully.
  • If there are permission errors, ensure that the Jenkins user has the correct SSH access and sudo privileges.

By following these steps, Jenkins will be able to securely connect to a remote server and execute Ansible playbooks, ensuring smooth automation in your DevOps pipeline.

Tiny Robot Unveiled to Detect and Treat Bowel Cancer

Parker Lennox
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0
Tiny Robot Unveiled to Detect and Treat Bowel Cancer

Unlock the Editor’s Digest for free

Scientists Build Tiny Gut Explorer Robot to Detect and Potentially Treat Lethal Common Cancer

Scientists have built a tiny gut explorer robot to detect and potentially treat a lethal common cancer, in the latest advance in the fast-evolving field of medical robotics.

How it works

The machine makes 3D scans of the colon that were previously impossible, using its mussel shell-like shape to roll through the digestive system when guided by a magnet outside the body. The innovation could boost detection of bowel cancer, which is treatable in its early stages but is the second-biggest cause of cancer deaths worldwide.

Potential Impact

"This minimally invasive robotic approach could significantly improve early diagnosis and, in future, allow targeted ultrasound-triggered medicine delivery," said Nikita Greenidge of Leeds university, lead author of a paper on the research published in Science Robotics on Wednesday.

Next Steps

Developers at Leeds, Glasgow and Edinburgh universities hope to launch human trials of the coin-sized robot next year, after successful testing on pigs.

Design and Functionality

The machine is 3D-printed from resin in a shape known as the oloid, which allows a wide range of movement and contact with surfaces. This means it can navigate and image the large intestine to an extent that was previously unattainable, the researchers said.

Advantages

The robot could enable virtual cancer screening that would eliminate delays, costs, and complications associated with traditional biopsy methods based on extracting bodily tissue, the authors write. Screening, diagnosis, and therapy could be carried out "in a single procedure" rather than the existing multi-stage processes lasting weeks or more.

Targeted Approach

The new method could be particularly helpful for women, the researchers say. Female colons are on average longer than their male equivalents, meaning standard screenings involving the insertion of a tube can be harder to carry out and more painful.

Industry Reaction

The project is an example of how cutting-edge technology is enabling the development of "rapid, non-invasive solutions that have the potential to revolutionise cancer diagnosis and treatment," said Jane Nicholson, executive director of research at the UK’s Engineering and Physical Sciences Research Council, which part-funded the work.

Conclusion

The tiny gut explorer robot has the potential to significantly improve early diagnosis and treatment of bowel cancer, a lethal common cancer that is the second-biggest cause of cancer deaths worldwide. If successful in human trials, this innovative technology could revolutionize cancer care, enabling virtual cancer screening and targeted treatment.

Frequently Asked Questions

Q: What is the purpose of the tiny gut explorer robot?
A: The robot is designed to detect and potentially treat bowel cancer, a lethal common cancer.

Q: How does the robot work?
A: The machine makes 3D scans of the colon using its mussel shell-like shape to roll through the digestive system when guided by a magnet outside the body.

Q: What are the potential benefits of the robot?
A: The robot could enable virtual cancer screening, eliminating delays, costs, and complications associated with traditional biopsy methods, and allowing for targeted ultrasound-triggered medicine delivery.

Q: When will human trials begin?
A: Developers hope to launch human trials of the robot next year, after successful testing on pigs.

Google Cooks Up Its Most Intelligent AI Model to Date

Taylor Marlowe
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0
Google Cooks Up Its Most Intelligent AI Model to Date

Gemini 2.5: Google DeepMind’s Most Intelligent AI Model to Date

Thinking Models: A New Era in AI

Google DeepMind has unveiled its latest AI model, Gemini 2.5, hailed as the most intelligent AI model to date. The first model from this generation is an experimental version of Gemini 2.5 Pro, which has achieved state-of-the-art results across a wide range of benchmarks.

Reasoning and Contextual Understanding

According to Koray Kavukcuoglu, CTO of Google DeepMind, the Gemini 2.5 models are "thinking models." This means they can reason through their thoughts before generating a response, leading to enhanced performance and improved accuracy. The capacity for "reasoning" extends beyond mere classification and prediction, encompassing the system’s ability to analyze information, deduce logical conclusions, incorporate context and nuance, and make informed decisions.

Enhanced Performance and Capabilities

Gemini 2.5 Pro has demonstrated state-of-the-art performance across various benchmarks that demand advanced reasoning. Notably, it leads in maths and science benchmarks, such as GPQA and AIME 2025, without relying on test-time techniques that increase costs. It also achieved a state-of-the-art score of 18.8% on Humanity’s Last Exam, a dataset designed by subject matter experts to evaluate the human frontier of knowledge and reasoning.

Coding Performance and Reasoning

Gemini 2.5 Pro excels in creating visually compelling web applications and agentic code applications, as well as code transformation and editing. On SWE-Bench Verified, the industry standard for agentic code evaluations, Gemini 2.5 Pro achieved a score of 63.8% using a custom agent setup. The model’s reasoning capabilities also enable it to create a video game by generating executable code from a single-line prompt.

Building on Previous Strengths

Gemini 2.5 builds upon the core strengths of earlier Gemini models, including native multimodality and a long context window. The model launches with a one million token context window, with plans to expand this to two million tokens soon. This enables the model to comprehend vast datasets and handle complex problems from diverse information sources, spanning text, audio, images, video, and even entire code repositories.

Availability and Feedback

Developers and enterprises can now begin experimenting with Gemini 2.5 Pro in Google AI Studio. Gemini Advanced users can access it via the model dropdown on desktop and mobile platforms. The model will be rolled out on Vertex AI in the coming weeks. Google DeepMind encourages users to provide feedback, which will be used to further enhance Gemini’s capabilities.

Conclusion

Gemini 2.5 represents a significant leap forward in AI research, enabling machines to reason, analyze, and make decisions like humans. Its ability to comprehend vast datasets, handle complex problems, and create code applications sets a new benchmark for AI performance. As the technology continues to evolve, it is likely to have a profound impact on various industries, including education, healthcare, and finance.

Frequently Asked Questions

Q: What is Gemini 2.5?
A: Gemini 2.5 is the latest AI model from Google DeepMind, hailed as the most intelligent AI model to date.

Q: What are the key features of Gemini 2.5?
A: Gemini 2.5 has the ability to reason, analyze, and make decisions like humans, with capabilities such as native multimodality, a long context window, and the ability to comprehend vast datasets.

Q: What are the applications of Gemini 2.5?
A: Gemini 2.5 has various applications, including creating visually compelling web applications, agentic code applications, code transformation, and editing.

Q: How can I access Gemini 2.5?
A: Developers and enterprises can access Gemini 2.5 Pro in Google AI Studio, while Gemini Advanced users can access it via the model dropdown on desktop and mobile platforms. The model will be rolled out on Vertex AI in the coming weeks.

How Extropic Plans to Unseat NVIDIA

Avery Winslow
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0
How Extropic Plans to Unseat NVIDIA

Revolutionizing Computing: A New Era of Scalable, Mass-Manufacturable, and Energy-Efficient Probabilistic Computing

A New Approach to Computation

Guillaume Verdon, CEO of Extropic, and his co-founder Trevor McCourt, are pushing the boundaries of computing with a revolutionary new platform. Their innovation lies in controlling thermodynamic effects in conventional silicon to perform calculations without extreme cooling. This approach is a game-changer, as it enables the development of a scalable, mass-manufacturable, and energy-efficient probabilistic computing platform.

Breaking Away from Traditional Computing

Traditional computing relies on superconducting electronic circuits to compute thermodynamically. However, Extropic’s approach uses fluctuations of electric charge in regular silicon, a more practical and cost-effective solution. This breakthrough has far-reaching implications for various industries, including finance, biology, and AI.

Monte Carlo Simulations: A Key Application

Monte Carlo simulations, a class of computation that involves sampling probabilities, is a key application of Extropic’s technology. These simulations are widely used in areas such as finance, biology, and AI, and are essential for building reasoning models like OpenAI o3 and Gemini 2.0 Flash Thinking from Google.

A Challenge to Nvidia’s Chip Dominance?

Extropic’s founders acknowledge that taking on Nvidia and other chipmakers might seem daunting. However, they believe that the current computing landscape, with its high energy consumption and environmental impact, makes it the perfect time to rethink how computers work. With AI companies building datacenters near nuclear power stations and nation-states investing heavily in AI, the potential for change is significant.

Conclusion

Extropic’s innovative approach to computing has the potential to revolutionize the industry. With its scalable, mass-manufacturable, and energy-efficient probabilistic computing platform, the company is poised to challenge traditional computing methods. As the world continues to grapple with the challenges of computing’s environmental impact, Extropic’s technology may be the key to a more sustainable future.

FAQs

Q: What is the significance of Extropic’s innovation?
A: Extropic’s innovation is a new approach to computing that uses fluctuations of electric charge in regular silicon, enabling the development of a scalable, mass-manufacturable, and energy-efficient probabilistic computing platform.

Q: What are the potential applications of Extropic’s technology?
A: Monte Carlo simulations, a class of computation that involves sampling probabilities, is a key application of Extropic’s technology. These simulations are widely used in areas such as finance, biology, and AI, and are essential for building reasoning models like OpenAI o3 and Gemini 2.0 Flash Thinking from Google.

Q: How does Extropic’s technology compare to traditional computing methods?
A: Extropic’s approach uses fluctuations of electric charge in regular silicon, whereas traditional computing relies on superconducting electronic circuits. This makes Extropic’s technology more practical and cost-effective.

Q: Can Extropic’s technology challenge Nvidia’s chip dominance?
A: While it may seem challenging, Extropic’s founders believe that the current computing landscape makes it the perfect time to rethink how computers work, and their technology has the potential to shake up the industry.

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