開発スタッフがアプリ関連の最新技術やニュースをご紹介します。

今回はGoogle AI StudioのTemperatureパラメータ設定について説明します。

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Microsoft is gearing up for its Build event with a preview online event, shifting the spotlight to AI advancements, particularly through its Copilot feature. The unveiling of the Surface Pro 10 for Business and Surface Laptop 6 for Business at this event puts Copilot front and center, with a dedicated key embedded in the keyboard. This move underscores Microsoft’s commitment to integrating AI into its hardware, making tasks like planning, document retrieval, and website analysis more accessible to users with a simple button press.

These new Surface PCs mark a significant step in Microsoft’s journey towards what they’re terming as “the first Surface PCs optimized for AI.” By incorporating Copilot directly into the keyboard, Microsoft demonstrates a deep investment in leveraging AI technology. While it’s still relatively early days for Copilot, with its launch just a year ago, this move signals a strategic alignment with the burgeoning trend of AI integration in computing devices. Despite the past presence of Cortana keys, Microsoft’s focus on Copilot underscores its dedication to enhancing user experiences through AI.

The industry at large has seen a surge in branding around AI, with terms like “AI PC” and “AI smartphones” becoming commonplace. While these labels may seem abstract to consumers, they reflect a broader push towards AI-powered functionalities. Microsoft’s approach of branding these Surface devices as “optimized for AI” strikes a balance between acknowledging the trend and providing tangible benefits to users. Ultimately, while a Copilot key may seem like a small addition, its presence underscores Microsoft’s commitment to integrating AI seamlessly into everyday computing tasks, all while respecting the constraints of physical device design.

Yuuma

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今回はGoogleのAI Studioの使用方法を紹介します。

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OpenAI has introduced Sora, an innovative generative AI model designed to transform text into video content. According to OpenAI, Sora can produce 1080p movie-like scenes featuring multiple characters, various types of motion, and detailed background elements, based on either brief or detailed text descriptions or still images. Additionally, Sora has the capability to “extend” existing video clips by filling in missing details.

The model’s proficiency lies in its deep understanding of language, enabling it to interpret prompts accurately and generate dynamic characters that convey vivid emotions. OpenAI emphasizes Sora’s comprehension not only of the user’s requests but also of how those elements manifest in the physical world.

Despite the lofty claims made by OpenAI, the showcased samples from Sora demonstrate impressive capabilities compared to other text-to-video technologies. Sora can produce videos up to a minute long in various styles, such as photorealistic, animated, or black and white, maintaining coherence and avoiding common pitfalls associated with AI-generated content.

However, Sora is not without flaws, as acknowledged by OpenAI. The model may struggle with accurately simulating complex scenes’ physics, understanding cause and effect relationships, or maintaining spatial and temporal consistency. OpenAI positions Sora as a research preview, refraining from making it generally available due to concerns about potential misuse.

OpenAI is actively collaborating with experts to identify and address potential vulnerabilities in the model and is developing tools to detect videos generated by Sora. Should OpenAI decide to make Sora publicly accessible, it pledges to include provenance metadata in generated outputs to mitigate misuse risks.

Yuuma

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Google Maps is set to revolutionize the way users discover new places with the introduction of a generative AI feature, as announced by the company. Leveraging large language models (LLMs), the feature analyzes a vast database of over 250 million locations on Google Maps and taps into contributions from over 300 million Local Guides. By employing a more conversational approach, users can make nuanced queries, such as seeking “places with a vintage vibe in SF,” and Maps will generate tailored recommendations for thrift shops, complete with categories, photo carousels, and review summaries.

Designed to be intuitive, the generative AI feature goes beyond conventional search experiences. Users can engage in a more dynamic interaction by asking follow-up questions. For example, if the initial query relates to vintage shops and is followed by “How about lunch?” the AI will seamlessly transition to finding restaurants that align with the user’s preferences, creating a more personalized and fluid exploration experience.

Google emphasizes the inclusivity of the new feature, asserting its capability to generate recommendations for even the most niche or specific queries. Initially launching as an early access experiment in the U.S., the feature will be accessible to select Local Guides—Google’s community contributors—before extending to a wider user base in the near future. While the company hasn’t disclosed the countries that will receive the feature, the move aligns with Google Maps’ evolving role from a navigation tool to a comprehensive platform for discovering and exploring new places.

This generative AI feature follows Google’s recent updates to Maps, which transformed the platform into a more sophisticated search tool, incorporating AI-powered features like photo results and suggesting specific places in response to ambiguous queries. Google envisions this innovation as just the starting point, expressing its commitment to further enhancing Maps with generative AI, solidifying its position as a go-to destination for exploration and discovery.

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