News from the AI & ML world
DeeperML - #openai
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Steve Newman@Second Thoughts
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New research suggests that the integration of AI coding tools into the development process may not be the productivity silver bullet many have assumed. A recent study conducted by METR, a non-profit AI benchmarking group, observed experienced open-source developers working on complex, mature codebases. Counterintuitively, the findings indicate that these AI tools actually slowed down task completion time by 19%. This slowdown is attributed to factors such as the time spent prompting the AI, waiting for responses, and meticulously reviewing and correcting the generated output. Despite this empirical evidence, many developers continued to use the tools, reporting that the work felt less effortful, even if it wasn't faster.
The study involved 16 seasoned developers and 246 real-world programming tasks. Before engaging with the AI tools, participants optimistically predicted a 24% increase in their productivity. However, after the trial, their revised estimates still overestimated the gains, believing AI had sped up their work by 20%, a stark contrast to the actual observed slowdown of 19%. Furthermore, fewer than 44% of the AI-generated code suggestions were accepted by the developers, with a significant portion of their time dedicated to refining or rewriting the AI's output. Lack of contextual knowledge and the complexity of existing repositories were cited as key reasons for the reduced effectiveness of the AI suggestions. While the study highlights a potential downside for experienced developers working on established projects, the researchers acknowledge that AI tools may offer greater benefits in other settings. These could include smaller projects, less experienced developers, or situations with different quality standards. This research adds a crucial layer of nuance to the broader narrative surrounding AI's impact on software development, suggesting that the benefits are not universal and may require careful evaluation on a case-by-case basis as the technology continues to evolve. Recommended read:
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M.G. Siegler@Spyglass
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In a significant development in the AI landscape, Google DeepMind has successfully recruited Windsurf's CEO, Varun Mohan, and key members of his R&D team. This strategic move follows the collapse of OpenAI's rumored $3 billion acquisition deal for the AI coding startup Windsurf. The unexpected twist saw Google swooping in to license Windsurf's technology for $2.4 billion and securing top talent for its own advanced projects. This development signals a highly competitive environment for AI innovation, with major players actively seeking to bolster their capabilities.
Google's acquisition of Windsurf's leadership and technology is primarily aimed at strengthening its DeepMind division, particularly for agentic coding projects and the enhancement of its Gemini model. Varun Mohan and co-founder Douglas Chen are expected to spearhead efforts in developing AI agents capable of writing test code, refactoring projects, and automating developer workflows. This integration is poised to boost Google's position in the AI coding sector, directly countering OpenAI's attempts to enhance its expertise in this critical area. The financial details of Google's non-exclusive license for Windsurf's technology have been kept confidential, but the substantial sum indicates the high value placed on Windsurf's innovations. The fallout from the failed OpenAI deal has left Windsurf in a precarious position. While the company remains independent and will continue to license its technology, it has lost its founding leadership and a portion of its technical advantage. Jeff Wang has stepped up as interim CEO to guide the company, with the majority of its 250 employees remaining. The situation highlights the intense competition and the fluid nature of talent acquisition in the rapidly evolving AI industry, where startups like Windsurf can become caught between tech giants vying for dominance. Recommended read:
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Rashi Shrivastava,@Rashi Shrivastava
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www.tomsguide.com
, Towards AI
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OpenAI is making significant strides in AI training and infrastructure. Sam Altman, CEO of OpenAI, envisions a new type of computer designed specifically for AI, suggesting current devices are not optimized for advanced AI capabilities. This new hardware aims to support always-on, context-aware AI assistants that can understand and act on a user's environment, schedule, and preferences in real-time. These AI-first computers could handle tasks like booking travel, summarizing content, and planning daily schedules through an intelligent interface.
OpenAI is also actively involved in initiatives to improve AI literacy. The company is backing a new AI training academy for teachers, indicating a focus on integrating AI more effectively into education. Furthermore, OpenAI continues to refine its language models, such as ChatGPT, for diverse applications, including creating and grading assignments within the classroom setting. This effort reflects a broader push to enhance coding workflows and other tasks. Adding to their suite of AI tools, OpenAI is reportedly preparing to launch a new AI-powered web browser. This browser is expected to rival Google Chrome, and is designed with a ChatGPT-like interface. Instead of traditional website navigation, interactions would be handled through the AI, streamlining tasks and potentially offering a more direct way to access information. Such a move could give OpenAI direct access to user data, which is crucial for enhancing their AI models and improving targeted advertising capabilities. Recommended read:
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Sean Endicott@windowscentral.com
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The Algorithmic Bridge
, www.windowscentral.com
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A recent MIT study has sparked debate about the potential cognitive consequences of over-reliance on AI tools like ChatGPT. The research suggests that using these large language models (LLMs) can lead to reduced brain activity and potentially impair critical thinking and writing skills. The study, titled "Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task," examined the neural and behavioral effects of using ChatGPT for essay writing. The findings raise questions about the long-term impact of AI on learning, memory, and overall cognitive function.
The MIT researchers divided 54 participants into three groups: one group that used ChatGPT exclusively, a search engine group, and a brain-only group relying solely on their own knowledge. Participants wrote essays on various topics over three sessions while wearing EEG headsets to monitor brain activity. The results showed that the ChatGPT group experienced a 32% lower cognitive load compared to the brain-only group. In a fourth session, participants from the ChatGPT group were asked to write without AI assistance, and their performance was notably worse, indicating a decline in independent writing ability. While the study highlights potential drawbacks, other perspectives suggest that AI tools don't necessarily make users less intelligent. The study's authors themselves acknowledge nuances, stating that the criticism of LLMs is supported and qualified by the findings, avoiding a black-and-white conclusion. Experts suggest that using ChatGPT strategically and not as a complete replacement for cognitive effort could mitigate the risks. They emphasized the importance of understanding the tools capabilities and limitations, focusing on augmentation rather than substitution of human skills. Recommended read:
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@www.marktechpost.com
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OpenAI has recently released an open-sourced version of a customer service agent demo, built using its Agents SDK. The "openai-cs-agents-demo," available on GitHub, showcases the creation of domain-specialized AI agents. This demo models an airline customer service chatbot, which adeptly manages a variety of travel-related inquiries by dynamically routing user requests to specialized agents. The system's architecture comprises a Python backend utilizing the Agents SDK for agent orchestration and a Next.js frontend providing a conversational interface and visual representation of agent transitions.
The demo boasts several focused agents including a Triage Agent, Seat Booking Agent, Flight Status Agent, Cancellation Agent, and an FAQ Agent. Each agent is meticulously configured with specific instructions and tools tailored to their particular sub-tasks. When a user submits a request, the Triage Agent analyzes the input to discern intent and subsequently dispatches the query to the most appropriate downstream agent. Guardrails for relevance and jailbreak attempts are implemented, ensuring topicality and preventing misuse. In related news, OpenAI CEO Sam Altman has claimed that Meta is aggressively attempting to poach OpenAI's AI employees with extravagant offers, including $100 million signing bonuses and significantly higher annual compensation packages. Despite these lucrative offers, Altman stated that "none of our best people have decided to take them up on that," suggesting OpenAI's culture and vision are strong factors in retaining talent. Altman believes Meta's approach focuses too heavily on monetary incentives rather than genuine innovation and a shared purpose, which he sees as crucial for success in the AI field. Recommended read:
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Chris McKay@Maginative
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OpenAI has secured a significant contract with the U.S. Defense Department, marking its first major foray into the national security sector. The one-year agreement, valued at $200 million, signifies a pivotal moment as OpenAI aims to supply its AI tools for administrative tasks and proactive cyberdefense. This initiative is the inaugural project under OpenAI's new "OpenAI for Government" program, highlighting the company's strategic shift and ambition to become a key provider of generative AI solutions for national security agencies. This deal follows OpenAI's updated usage policy, which now permits defensive or humanitarian military applications, signaling a departure from its earlier stance against military use of its AI models.
This move by OpenAI reflects a broader trend in the AI industry, with rival companies like Anthropic and Meta also embracing collaborations with defense contractors and intelligence agencies. OpenAI emphasizes that its usage policy still prohibits weapon development or kinetic targeting, and the Defense Department contract will adhere to these restrictions. The "OpenAI for Government" program includes custom models, hands-on support, and previews of product roadmaps for government agencies, offering them an enhanced Enterprise feature set. In addition to its government initiatives, OpenAI is expanding its enterprise strategy by open-sourcing a new multi-agent customer service demo on GitHub. This demo showcases how to build domain-specialized AI agents using the Agents SDK, offering a practical example for developers. The system models an airline customer service chatbot capable of handling various travel-related queries by dynamically routing requests to specialized agents like Seat Booking, Flight Status, and Cancellation. By offering transparent tooling and clear implementation examples, OpenAI aims to accelerate the adoption of agentic systems in everyday enterprise applications. Recommended read:
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Mark Tyson@tomshardware.com
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OpenAI has launched O3 PRO for ChatGPT, marking a significant advancement in both performance and cost-efficiency for its reasoning models. This new model, O3-Pro, is now accessible through the OpenAI API and the Pro plan, priced at $200 per month. The company highlights substantial improvements with O3 PRO and has also dropped the price of its previous o3 model by 80%. This strategic move aims to provide users with more powerful and affordable AI capabilities, challenging competitors in the AI model market and expanding the boundaries of reasoning.
The O3-Pro model is set to offer enhanced raw reasoning capabilities, but early reviews suggest mixed results when compared to competing models like Claude 4 Opus and Gemini 2.5 Pro. While some tests indicate that Claude 4 Opus currently excels in prompt following, output quality, and understanding user intentions, Gemini 2.5 Pro is considered the most economical option with a superior price-to-performance ratio. Initial assessments suggest that O3-Pro might not be worth the higher cost unless the user's primary interest lies in research applications. The launch of O3-Pro coincides with other strategic moves by OpenAI, including consolidating its public sector AI products under the "OpenAI for Government" banner, including ChatGPT Gov. OpenAI has also secured a $200 million contract with the U.S. Department of Defense to explore AI applications in administration and security. Despite these advancements, OpenAI is also navigating challenges, such as the planned deprecation of GPT-4.5 Preview in the API, which has caused frustration among developers who relied on the model for their applications and workflows. Recommended read:
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Chris McKay@Maginative
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OpenAI has secured a significant one-year, $200 million contract with the U.S. Defense Department, marking a turning point for the company after previously refraining from military applications of its AI technology. This deal officially launches the "OpenAI for Government" initiative, a program aimed at supplying AI tools to national-security agencies. The Pentagon confirmed the deal on Monday, stating that OpenAI will develop AI prototypes to tackle critical national security challenges across both warfighting and enterprise domains, signaling a major push to supply generative AI to these sectors.
The "OpenAI for Government" program consolidates OpenAI's existing public sector products, including ChatGPT Gov, and partnerships with entities like the U.S. National Labs and the Air Force Research Laboratory. This initiative promises custom AI models, hands-on support, and insights into OpenAI's future developments for agencies willing to invest in its technology. The Defense Department intends to leverage OpenAI for Government to explore AI applications in administration and security, including enhancing healthcare portals, improving program and acquisition data searches, and bolstering proactive cyber defense measures. Despite venturing into defense applications, OpenAI emphasizes that all use cases must adhere to its established usage policies and guidelines, which prohibit activities such as weapons development and kinetic targeting. OpenAI's national security lead, Katrina Mulligan, affirmed that this initiative aims to accelerate the U.S. government's adoption of AI and deliver impactful AI solutions for the American people, while remaining within ethical boundaries. The contract represents a strategic move for OpenAI, positioning itself as a key AI vendor for federal, state, and local government entities. Recommended read:
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@www.unite.ai
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www.techradar.com
, www.tomsguide.com
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OpenAI has significantly upgraded ChatGPT's Projects feature, introducing a suite of new tools designed to enhance productivity and streamline workflows. This update marks the most substantial improvement to Projects since its initial launch, transforming it from a simple organizational tool into a smarter, more context-aware workspace. Users can now leverage features like voice mode, enhanced memory, and mobile file uploads to manage research, code repositories, and creative endeavors more efficiently. The implications for professionals and anyone managing complex tasks are considerable.
The upgraded Projects feature now includes six key enhancements. Voice Mode allows users to engage in discussions about files and past chats hands-free, enabling activities like reviewing reports while walking or brainstorming during commutes. Enhanced memory ensures ChatGPT retains context from previous conversations and documents within a project, eliminating the need for repetitive explanations. The ability to upload files directly from mobile devices offers greater flexibility and convenience. Furthermore, Projects now supports Deep Research, providing more in-depth analysis and insights. Users can also set project-specific instructions that override general custom instructions, ensuring a tailored experience. These updates collectively transform Projects into a centralized hub where chats, files, and instructions coexist within a focused workspace, making it ideal for larger, iterative tasks requiring deeper context and potential collaboration. OpenAI aims for Projects to function more like smart workspaces than one-off chats. Recommended read:
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Chris McKay@Maginative
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Meta is making a significant move in the artificial intelligence race, investing $14.3 billion for a 49% stake in data-labeling startup Scale AI. This deal is more than just a financial investment; it brings Scale AI's CEO, 28-year-old Alexandr Wang, into Meta to lead a new "superintelligence" lab. The move highlights Meta's ambition to develop AI that surpasses human capabilities across multiple domains and is a calculated gamble to regain momentum in the competitive AI landscape. Meta is aiming for an AI reset and hopes that Scale's Wang is the right partner.
This acquisition reflects Meta's strategic shift towards building partnerships and leveraging external talent. Scale AI isn't a well-known name to the general public, but it's a vital component in the AI industry, providing the labeled training data that powers many AI systems, including those used by OpenAI, Microsoft, Google, and even the U.S. Department of Defense. Meta has agreed to dramatically increase its spending with Scale, but one person said Scale expects some other companies like Google and OpenAI will stop using Scale's services for fear of Meta using information about their usage to gain a competitive advantage. The "superintelligence" lab is part of a larger reorganization of Meta's AI divisions, aimed at sharpening the company's focus after facing internal challenges and criticism over its AI product releases. Meta, under CEO Mark Zuckerberg, has been heavily investing in AI infrastructure and product development since the rise of ChatGPT, launching its own large language model family, Llama. Zuckerberg has been personally recruiting top researchers to boost its AI efforts. The new lab will focus on developing a theoretical form of AI that surpasses human cognitive capabilities, a long-term and highly speculative goal that Meta is now seriously pursuing. Recommended read:
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@www.microsoft.com
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academy.towardsai.net
, pub.towardsai.net
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Microsoft and Towards AI are addressing the AI skills gap with a new course, "AI for Business Professionals," designed to help professionals move beyond basic AI usage to achieve significant improvements in work quality and innovation. This initiative comes as organizations increasingly recognize generative AI as a game-changer but struggle with effective adoption due to a lack of strategic knowledge and technical skills among their teams. The course aims to transform individuals from merely AI-curious to AI-skilled collaborators, enabling them to use AI not just for speed, but to generate innovative ideas and achieve exceptional quality in their work.
The "AI for Business Professionals" course offers practical training tailored for diverse roles, including software engineers and investment research analysts. It provides modules and actionable strategies designed to optimize coding, streamline administrative tasks, and identify groundbreaking opportunities using AI. The self-paced course includes short videos, hands-on exercises, real-world demos, and expert guidance, all designed for busy, non-technical professionals. Participants will learn how to use AI deeply, effectively, and strategically in their daily work, addressing common issues such as distrust in AI output and uncertainty about time savings. Microsoft emphasized the importance of continuous learning and career development in keeping up with evolving business needs. Nearly half (47%) of businesses say their top workforce strategy over the next 12 to 18 months is to train their existing workforce in AI skills. The course aims to provide individuals with the opportunity to develop the AI skills they need to build confidence, establish fluency, and thrive in the new AI economy. A free lesson is available to preview the course's content and learn how to use AI effectively, and strategically in daily work. The full course is available for $399. Recommended read:
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Brandon Vigliarolo@The Register - Software
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ChatGPT experienced a major global outage on June 10, 2025, causing disruptions for users worldwide. OpenAI confirmed elevated error rates and latency across its services, including ChatGPT, the Sora text-to-video product, and its APIs. Users reported that prompts were either taking significantly longer to be answered or were met with an error message. The issue started around 3:00 AM Eastern Time, with reports on Downdetector steadily climbing as the morning progressed and the United States woke up. Downdetector indicated the problems were not restricted to the United States, with users in other countries reporting similar issues.
OpenAI stated that they had identified the root cause of the issue and were working on implementing a fix. According to the company's status page, the login services appeared to be functioning normally, but other services were experiencing partial outages. A separate entry for elevated error rates in Sora was also included on the status page. Initially, some users appeared to regain access around 6:00 AM ET, but reports of issues soon returned. Later in the day, OpenAI reported that the fix was underway, with API calls in the process of recovering. However, the company also stated that full access to other affected services, including ChatGPT, could take "another few hours." While user reports on Down Detector initially dipped, it remained to be seen whether this signaled the outage ramping down or if further spikes would occur. OpenAI's service status later switched from red to yellow as the company reported that ChatGPT and API calls were slowly recovering, with Sora back to full operation. Recommended read:
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Carl Franzen@AI News | VentureBeat
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Mistral AI has launched its first reasoning model, Magistral, signaling a commitment to open-source AI development. The Magistral family features two models: Magistral Small, a 24-billion parameter model available with open weights under the Apache 2.0 license, and Magistral Medium, a proprietary model accessible through an API. This dual release strategy aims to cater to both enterprise clients seeking advanced reasoning capabilities and the broader AI community interested in open-source innovation.
Mistral's decision to release Magistral Small under the permissive Apache 2.0 license marks a significant return to its open-source roots. The license allows for the free use, modification, and distribution of the model's source code, even for commercial purposes. This empowers startups and established companies to build and deploy their own applications on top of Mistral’s latest reasoning architecture, without the burdens of licensing fees or vendor lock-in. The release serves as a powerful counter-narrative, reaffirming Mistral’s dedication to arming the open community with cutting-edge tools. Magistral Medium demonstrates competitive performance in the reasoning arena, according to internal benchmarks released by Mistral. The model was tested against its predecessor, Mistral-Medium 3, and models from Deepseek. Furthermore, Mistral's Agents API's Handoffs feature facilitates smart, multi-agent workflows, allowing different agents to collaborate on complex tasks. This enables modular and efficient problem-solving, as demonstrated in systems where agents collaborate to answer inflation-related questions. Recommended read:
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Mark Tyson@tomshardware.com
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OpenAI has recently launched its newest reasoning model, o3-pro, making it available to ChatGPT Pro and Team subscribers, as well as through OpenAI’s API. Enterprise and Edu subscribers will gain access the following week. The company touts o3-pro as a significant upgrade, emphasizing its enhanced capabilities in mathematics, science, and coding, and its improved ability to utilize external tools.
OpenAI has also slashed the price of o3 by 80% and o3-pro by 87%, positioning the model as a more accessible option for developers seeking advanced reasoning capabilities. This price adjustment comes at a time when AI providers are competing more aggressively on both performance and affordability. Experts note that evaluations consistently prefer o3-pro over the standard o3 model across all categories, especially in science, programming, and business tasks. O3-pro utilizes the same underlying architecture as o3, but it’s tuned to be more reliable, especially on complex tasks, with better long-range reasoning. The model supports tools like web browsing, code execution, vision analysis, and memory. While the increased complexity can lead to slower response times, OpenAI suggests that the tradeoff is worthwhile for the most challenging questions "where reliability matters more than speed, and waiting a few minutes is worth the tradeoff.” Recommended read:
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Mark Tyson@tomshardware.com
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OpenAI has launched o3-pro, a new and improved version of its AI model designed to provide more reliable and thoughtful responses, especially for complex tasks. Replacing the o1-pro model, o3-pro is accessible to Pro and Team users within ChatGPT and through the API, marking OpenAI's ongoing effort to refine its AI technology. The focus of this upgrade is to enhance the model’s reasoning capabilities and maintain consistency in generating responses, directly addressing shortcomings found in previous models.
The o3-pro model is designed to handle tasks requiring deep analytical thinking and advanced reasoning. While built upon the same transformer architecture and deep learning techniques as other OpenAI chatbots, o3-pro distinguishes itself with an improved ability to understand context. Some users have noted that o3-pro feels like o3, but is only modestly better in exchange for being slower. Comparisons with other leading models such as Claude 4 Opus and Gemini 2.5 Pro reveal interesting insights. While Claude 4 Opus has been praised for prompt following and understanding user intentions, Gemini 2.5 Pro stands out for its price-to-performance ratio. Early user experiences suggest o3-pro might not always be worth the expense due to its speed, except for research purposes. Some users have suggested that o3-pro hallucinates modestly less, though this is still being debated. Recommended read:
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