Google DeepMind will support Anthropic's Model Card Protocol (MCP) for its Gemini AI model and software development kit (SDK). This move aims to standardize how AI models interact with external data sources and tools, improving transparency and facilitating safer development. By adopting the open standard, Google hopes to make it easier for developers to build and deploy AI applications responsibly, while promoting interoperability between different AI models. This collaboration signifies growing industry interest in standardized practices for AI development.
SMBC is ending its partnership with Hiveworks after ten years. Zach Weiner, the creator of SMBC, expresses gratitude for Hiveworks' support in growing the comic and handling business aspects, allowing him to focus on the creative side. He emphasizes that the split is amicable and driven by a desire to explore new opportunities and have more direct control over SMBC's future. While the comic's URL and format will remain the same, behind-the-scenes operations are changing. Weiner looks forward to maintaining a positive relationship with Hiveworks and is excited about the next chapter for SMBC.
Several Hacker News commenters expressed surprise and disappointment at SMBC's departure from Hiveworks, with some speculating about the reasons behind the split. Some wondered if it was due to financial disagreements or creative differences. Others praised Zach Weinersmith's talent and entrepreneurial spirit, wishing him well in his independent venture. A few commenters mentioned missing the collaborative nature of Hiveworks and hoped other creators wouldn't follow suit. Several also lamented the loss of the Hiveworks unified RSS feed and the convenience it offered. The potential difficulties of self-publishing, particularly regarding advertising and merchandise management, were also brought up. There was general agreement that the change would be a significant undertaking for Weinersmith.
Waymo's autonomous ride-hailing service is now available on the Uber app in Austin, Texas. This expansion offers Uber users the option to hail a fully autonomous ride, powered by Waymo's fifth-generation Waymo Driver, in select central areas of the city. Initially, rides will be provided in a "rider-only" configuration with no human driver present, but future plans include testing rides with a trained vehicle operator. This partnership builds on previous collaborations between Waymo and Uber in Phoenix and San Francisco.
HN commenters are generally positive about the Waymo-Uber partnership, viewing it as a pragmatic and beneficial move for both companies. Some express surprise, given the prior contentious lawsuit between them, but see this as a sign of maturity and a focus on customer benefit. Several commenters highlight the potential for increased competition and innovation in the autonomous vehicle space, leading to better service and wider availability for consumers. A few raise concerns about potential monopolies forming and the long-term implications for drivers, but the overall sentiment is one of cautious optimism about the collaboration. Several commenters also speculate about the technical and logistical challenges of integrating the two systems, and question the specifics of the revenue sharing model.
Schrödinger, a computational drug discovery company partnering with Nvidia, is using AI and physics-based simulations to revolutionize pharmaceutical development. Their platform accelerates the traditionally slow and expensive process of identifying and optimizing drug candidates by predicting molecular properties and interactions. Nvidia CEO Jensen Huang encouraged Schrödinger to expand their ambition beyond drug discovery, envisioning applications in materials science and other fields leveraging their computational prowess and predictive modeling capabilities. This partnership combines Schrödinger's scientific expertise with Nvidia's advanced computing power, ultimately aiming to create a new paradigm of accelerated scientific discovery.
Hacker News users discuss Nvidia's partnership with Schrödinger and their ambitious goals in drug discovery. Several commenters express skepticism about the feasibility of using AI to revolutionize drug development, citing the complexity of biological systems and the limitations of current computational methods. Some highlight the potential for AI to accelerate specific aspects of the process, such as molecule design and screening, but doubt it can replace the need for extensive experimental validation. Others question the hype surrounding AI in drug discovery, suggesting it's driven more by marketing than scientific breakthroughs. There's also discussion of Schrödinger's existing software and its perceived strengths and weaknesses within the field. Finally, some commenters note the potential conflict of interest between scientific rigor and the financial incentives driving the partnership.
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https://news.ycombinator.com/item?id=43646227
Hacker News commenters discuss the implications of Google supporting Anthropic's Model Card Protocol (MCP), generally viewing it as a positive move towards standardization and interoperability in the AI model ecosystem. Some express skepticism about Google's commitment to open standards given their past behavior, while others see it as a strategic move to compete with OpenAI. Several commenters highlight the potential benefits of MCP for transparency, safety, and responsible AI development, enabling easier comparison and evaluation of models. The potential for this standardization to foster a more competitive and innovative AI landscape is also discussed, with some suggesting it could lead to a "plug-and-play" future for AI models. A few comments delve into the technical aspects of MCP and its potential limitations, while others focus on the broader implications for the future of AI development.
The Hacker News post titled "Hassabis Says Google DeepMind to Support Anthropic's MCP for Gemini and SDK" has generated a moderate number of comments, primarily focusing on the strategic implications of Google's adoption of Anthropic's Model Card Protocol (MCP) for their Gemini AI model. Several commenters express skepticism about the genuine openness of this move, suspecting it's more about competitive positioning and control rather than a true embrace of interoperability.
One compelling line of discussion revolves around the idea that Google is attempting to co-opt the MCP standard, potentially influencing its future development in a way that benefits Google's ecosystem. Commenters speculate that Google might subtly steer the MCP towards compatibility with their own tools and infrastructure, making it more difficult for competitors to integrate seamlessly. This raises concerns about the long-term implications for a truly open and interoperable AI landscape.
Another significant point raised is the potential for "embrace, extend, extinguish," a strategy where a company adopts a standard, extends it in proprietary ways, and eventually renders the original standard obsolete. Commenters question whether Google's commitment to MCP is genuine or if it's a tactic to gain control and eventually push their own solutions.
There's also discussion about the practical implications of using MCP. Some commenters express doubts about the effectiveness of model cards in conveying the nuances of complex AI models, suggesting that they might oversimplify or misrepresent the model's capabilities and limitations.
A few comments touch upon the broader context of the competitive AI landscape, with some suggesting that this move by Google is a direct response to the growing influence of open-source models and platforms. By supporting MCP, Google might be trying to create a more controlled environment for AI development, potentially limiting the impact of open-source alternatives.
Finally, some commenters express cautious optimism, hoping that Google's adoption of MCP will genuinely contribute to greater transparency and interoperability in the AI field. However, the overall sentiment seems to be one of cautious skepticism, with many commenters emphasizing the need to carefully observe Google's actions to determine their true intentions.