Harvey AI, a legal tech startup supported by OpenAI, has successfully raised $300 million in a Series E funding round. This significant investment underscores the growing interest in artificial intelligence applications within the legal industry. The funding will be used to enhance Harvey’s platform, which leverages AI to streamline legal research and document drafting, improving efficiency for law firms and legal professionals. The startup aims to revolutionize traditional legal practices by integrating advanced technology, making legal services more accessible and efficient. With this latest round of financing, Harvey AI is well-positioned to expand its offerings and solidify its presence in the competitive legal tech market. The backing from OpenAI highlights the increasing collaboration between technology and legal sectors, paving the way for innovative solutions that meet the demands of modern legal work.
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Harvey AI, Backed by OpenAI, Secures $300M in Series E Funding – Tech in Asia
OpenAI’s Upcoming AI Device Will Not Be Wearable, According to Legal Documents
Recent legal filings reveal that OpenAI and Jony Ive’s design team, io, are collaborating on a consumer AI device, with a planned launch no earlier than 2026. The prototype, referenced by OpenAI CEO Sam Altman, is still over a year away from sale and will not be an in-ear or wearable device. Tang Tan, io’s chief hardware officer, noted that the design is not finalized yet. OpenAI recently acquired io for $6.5 billion, but had to remove public mentions of the io brand due to a trademark dispute with an audio startup named Iyo. Legal documents indicate that OpenAI and io were aware of Iyo’s competing “audio computer” and had conducted extensive research into in-ear devices, having purchased over 30 headphone models for evaluation. Altman described the prototype as a pocket-sized or desk-friendly device capable of understanding its environment, confirming that multiple form factors are under consideration.
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Court Documents Reveal Details of OpenAI’s AI Hardware Collaboration with Jony Ive
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Understanding Inference in AI: Insights from Google Experts
The content presents two surveys – one focused on Google AI product usage and the other on article improvements. The first survey, titled “AA – Google AI product use – I/O,” targets users of Google AI tools like Gemini and NotebookLM, asking participants how frequently they use these tools, with options ranging from daily to unsure. This survey is designed to be displayed with a 75% rate after a scroll depth trigger of 50%.
The second survey, “Article Improvements – March 2025,” seeks feedback on enhancing articles. It poses a question about potential improvements, offering responses such as making content more concise, adding details, or including multimedia. This survey also has a 75% display rate and a scroll depth trigger of 75%. Both surveys conclude with a thank-you message and an emoji, aiming to gather user insights to improve product engagement and content quality.
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Zendy Insights | Explore Our Blog
Zendy has announced the inclusion of Wiley and IEEE in its revenue-sharing model based on Retrieval-Augmented Generation (RAG), promoting ethical AI collaboration in academic publishing. This expansion follows previous announcements and showcases a shift towards partnerships in AI, as these prominent publishers join others to ensure fair compensation when licensed content is referenced. Zendy’s AI assistant, ZAIA, can now access a richer pool of peer-reviewed material, enhancing the quality and attribution of research outputs. Co-founder Kamran Kardan highlights this as a pivotal moment in AI-Publisher relations, advocating a transparent model that integrates publishers into the AI ecosystem. This approach not only supports researcher integrity but also addresses the needs of the broader scholarly community by providing reliable access to high-quality information. Zendy invites all stakeholders to participate in defining ethical AI practices that fortify scholarly communication. For more information, visit their website.
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Mind Meld: Two Weeks with ChatGPT and Claude
The author reflects on their transformative experience with AI, dubbing it the “Mind Melt.” Initially skeptical, they discovered the immense productivity boost AI offered while alone for two weeks. Engaging with multiple chatbots—ChatGPT, Claude, Gemini, and Copilot—led to significant breakthroughs in creativity and tech management. AI assisted in generating ideas for short films, recommending software, and troubleshooting server issues, effectively becoming a creative partner. The author highlights two “killer apps”: one for creative brainstorming and another for tech support, noting that collaborative work with AI feels like a renaissance. They share insights on each chatbot’s strengths, with ChatGPT excelling in writing, Claude in coding, and Gemini providing methodical explanations. As their productivity soared, the author experienced both excitement and burnout, concluding that AI significantly extends their skill set and reshapes their approach to work, highlighting the potential for various applications across fields.
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Cognitive Debt Accumulation in Essay Writing with AI Assistants — MIT Media Lab
This study investigates the effects of LLM-assisted essay writing on neural and behavioral aspects. Participants were split into three groups: LLM, Search Engine, and Brain-only (no tools), completing three sessions each, followed by a fourth session with group reassignment. A total of 54 participants were involved, with 18 completing all sessions. Electroencephalography (EEG) measured cognitive load, while essays were analyzed using Natural Language Processing (NLP) and scored by human teachers and an AI judge. Results indicated significant differences in brain connectivity, with Brain-only users showing the strongest networks, while LLM users exhibited the weakest. In the final session, LLM-to-Brain participants showed decreased neural engagement, whereas Brain-to-LLM users demonstrated improved memory recall. Ownership of essays was lowest among LLM users, who also struggled with quoting their work. Findings suggest that despite the convenience of LLMs, they may incur cognitive costs, raising concerns about their long-term educational impact and the role of AI in learning.
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Colgate Unleashes AI Tool to Unlock Behavioral Insights for Premium Strategy
Colgate-Palmolive, in collaboration with the Indian Dental Association, launched the ‘Oral Health Movement’ to address the widespread gum problems in India, where 50% are affected but only 10% are aware. The tech-driven initiative, utilizing an AI screening tool accessible via WhatsApp or the Colgate website, has already screened 4.5 million people. The platform provides personalized oral health assessments and emphasizes the link between oral health and systemic conditions like heart disease and diabetes. Extensive outreach has reached 550 million people through QR codes on products. Despite low awareness, rural states like UP and Bihar showed unexpected engagement. Colgate, adhering to a consumer-first strategy, is navigating channel conflicts in the market while prioritizing data privacy in health data handling. The company aims to expand its premium product offerings and advocates for broader dental insurance coverage, acknowledging the challenge of growing in a saturated market.
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Users’ Private Conversations Exposed on App’s Public Feed: A Major Blow for Instagram’s Parent Company
Mark Zuckerberg’s entry into AI chatbots has led to significant privacy concerns, with users’ private conversations unintentionally shared on a public newsfeed through the Meta.ai platform. This feature allows users to opt-in to sharing but could confuse many, as it requires only two steps to activate. Consequently, sensitive personal information, including financial and custody details, may be exposed alongside real Facebook or Instagram identities. While Zuckerberg suggests AI can fulfill social and emotional needs better than human connections, former Instagram executive Meghana Dhar argues that such platforms have exacerbated loneliness rather than alleviating it. Meta’s ambitious AI strategy is underscored by a recent $14.3 billion acquisition aimed at boosting its technology, despite leading to conflicts with rivals like OpenAI. Additionally, Zuckerberg’s shifting public persona reflects a broader ideological transformation within Meta, raising further scrutiny regarding its influence and direction.
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Practical Adversarial AI: Comprehensive Resources for Mastering Adversarial Machine Learning and Security Vulnerabilities
This project provides a flexible, stand-alone educational course or a practical component for university-level studies in adversarial AI and machine learning. Originating from Dr. Allison Bishop’s lectures at the City College of New York, it requires familiarity with Python 3.7+, basic data structures and algorithms, and introductory calculus and probability. The materials are designed to be self-contained, without the need for prior machine learning experience. The course covers three key parts: classical adversarial thinking, neural network fundamentals focusing on building CNNs with PyTorch, and an exploration of adversarial examples and attacks like FGSM and PGD. To get started, users can clone the repository, set up their environment, and access the content via Jupyter Notebook. The materials are intended solely for educational purposes, helping students understand and mitigate the security vulnerabilities in machine learning. Proper citation is requested for any academic use.
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