Category: Artificial intelligence

  • Japan Invests $65 Billion to Boost Semiconductor Industry

    Japan Invests $65 Billion to Boost Semiconductor Industry

    Japanese Prime Minister Shigeru Ishiba has unveiled an impressive plan worth 10 trillion yen (approximately $65 billion) aimed at rejuvenating Japan’s semiconductor and AI sectors. This substantial investment strategy is set to be introduced to parliament and intends to boost local chip production by the year 2030.

    Focus on Rapidus and AI Chips

    A key element of this initiative is the Rapidus project, which is Japan’s emerging chip manufacturing endeavor, alongside other firms focused on AI semiconductors. Rapidus commenced in 2022 with support from the government and eight leading companies, targeting mass production of 2-nanometer chips by 2027 in Hokkaido. To achieve this goal, they have formed partnerships with IBM and the Belgian research organization Imec.

    Economic Expectations

    The government anticipates a considerable economic effect, aspiring to generate around 160 trillion yen (close to $1 trillion) in financial benefits. They foresee approximately 50 trillion yen ($322 million) in total investment from both public and private sectors for semiconductor advancement over the next decade.

    Funding without Bonds

    Interestingly, Ishiba has noted that they won’t be utilizing deficit-covering bonds for financing this project. While he didn’t elaborate on the sources of funding, it’s evident that this marks a significant rise from Japan’s previous 2 trillion yen ($12.9 billion) investment in its semiconductor industry, highlighting the country’s commitment to regaining a prominent position in the global chip market.

    This initiative arrives as nations worldwide are working to strengthen their supply chains in response to recent market challenges and ongoing trade tensions between the U.S. and China. The entire economic package, which includes these semiconductor initiatives, is scheduled for cabinet approval on November 22. This is Japan’s most daring strategy in years to reclaim its status as a frontrunner in advanced chip manufacturing, reminiscent of its past dominance during the 1980s and 1990s.

    Source: Link

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  • Slack Develops AI File Summary Feature for Enhanced Productivity

    Slack Develops AI File Summary Feature for Enhanced Productivity

    Slack is said to be developing a new AI feature that will summarize documents uploaded by users. Back in February 2024, the platform launched Slack AI, which came with tools for summarizing chat threads, providing contextual search, and offering channel recaps that highlight important information users may have missed.

    New Feature Discovery

    A report from Android Authority indicates that Slack aims to enhance its features with the addition of AI file summaries. The publication performed an APK teardown on the latest Android version of Slack (24-10-50-0) and found several code strings that hint at this new feature.

    Limitations and Requirements

    Two of the code strings, and , imply that there will be certain restrictions, such as limitations on document size or if the file is password protected. Another string, , suggests that the feature may require documents to meet a minimum word count to be eligible for summarization.

    User Feedback and Control

    Users will also have the option to delete AI-generated summaries and provide feedback on them, indicating whether the information was "inaccurate" or if it "had too much or too little detail." As of now, Slack has not officially announced anything regarding this upcoming feature.

    Source: Link,Link

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  • Amazon Invests in AI Chips to Decrease Nvidia Dependence

    Amazon Invests in AI Chips to Decrease Nvidia Dependence

    Amazon is set to launch its next-generation Trainium 2 AI chip next month, promising performance improvements of up to four times compared to the original version.

    Development and Acquisition

    According to The Financial Times, the chip was designed by Annapurna Labs, a microelectronics startup from Israel that Amazon bought in 2015. The goal behind this acquisition is to develop chips that can compete with Nvidia’s products and lessen the company’s reliance on Nvidia.

    In an interview with Financial Times, Dave Brown, who is the vice-president of compute and networking services at AWS, mentioned their ambition to be “absolutely the best place to run Nvidia, but at the same time we think its healthy to have an alternative.”

    Market Dynamics

    Nvidia currently dominates the AI chip market, holding an impressive 80% share and recording $26.3 billion in revenue from chip sales in the second quarter of fiscal 2024. Amazon plans to invest around $75 billion in capital throughout 2024, primarily for technology and infrastructure, with expectations to increase spending in 2025.

    While Amazon doesn’t provide independent performance benchmarks for its chips, it stated that its “Inferentia” chips, which are designed for specific tasks, cost 40% less to operate when generating AI responses.

    System Integration

    As Remi Sinno, a former employee of Softbank and Intel who is now the engineering director at Annapurna, puts it, “It’s not [just] about the chip, it’s about the full system.”

    Sinno also added, “it’s really hard to do what we do at scale. Not too many companies can.”

    Source: Link,Link

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  • Baidu Launches I-RAG, Miaoda, and Innovative Smart Glasses

    Baidu Launches I-RAG, Miaoda, and Innovative Smart Glasses

    Chinese AI and internet company Baidu has revealed new AI-driven software and hardware during its annual Baidu World Conference. Similar to Google, Baidu stands as China’s top search engine, and over the years, it has gradually expanded its business to encompass AI technologies.

    Launch of New Innovations

    As per a report from Reuters, after investing heavily in AI for the past two years, Baidu has introduced its initial image generator and a no-code platform. They also mentioned that their AI chatbot, Ernie, manages to answer over 1.5 billion user inquiries each day.

    Features of New Tools

    The firm claims that its latest text-to-image tool, known as I-RAG, reduces the chances of “hallucinations” in visuals while utilizing the search engine to enhance prompts and image results.

    Miaoda, the no-code platform, is said to enable individuals without programming skills to create application prototypes. The company states that it will leverage the Ernie LLM to produce code that’s simple to modify and adjust.

    Additional Hardware Showcase

    In addition to the software innovations, Baidu also presented smart glasses from its hardware branch, Xiaodu. These glasses feature an AI assistant that operates on the Ernie Foundation model and will work in conjunction with services such as Baidu Maps and Baike.

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  • India Tops AI Adoption at 30%: New Research Insights

    India Tops AI Adoption at 30%: New Research Insights

    India is at the forefront of embracing new AI technologies, with an adoption rate of 30% compared to the global average of 26%. A study by the Boston Consulting Group (BCG), referenced by ANI News, reveals that sectors such as fintech, software, and banking in India are investing heavily in AI to boost their revenue.

    Research Insights

    The report titled "Where’s the value in AI?" is founded on insights from 1,000 Chief Experience Officers and senior executives across 20 industries, covering 59 countries in Asia, Europe, and North America. It highlights that only 4% of businesses worldwide can consistently create value through AI technologies. Moreover, 22% have implemented an AI strategy, while almost 74% have yet to see any real benefits from their investments in this area.

    Expert Opinions

    In an interview with ANI News, Saibal Chakraborty, the head of technology and Digital Advantage Practice at BCG in India, mentioned that the country’s use of AI is "transforming its competitive stance on the global stage," with 30% of Indian firms fully realizing AI’s value potential, which is above the global average of 26%.

    Chakraborty also noted that "India is unique in its willingness to leverage AI’s capabilities" and believes that "the country is in a strong position to not just adopt AI but also to generate significant and measurable outcomes."

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  • OpenAI Faces Challenges in Collecting Training Data for Models

    OpenAI Faces Challenges in Collecting Training Data for Models

    OpenAI appears to be facing a challenge in enhancing the performance of its upcoming AI models. The company’s next significant model, "Orion," is said to be lagging in certain tasks when compared to its earlier models.

    Advantages in Language Tasks

    While "Orion" excels in language-related tasks like translation and text generation, it has not performed well in areas such as coding. This inconsistency raises concerns about its overall effectiveness in diverse applications.

    Challenges with Training Data

    A report from The Information (cited by Gadgets360) indicates that there are difficulties in collecting training data for these new models. Additionally, running this model in data centers is more costly than operating GPT-4 and GPT-4o.

    The improvement in quality is also not as pronounced as the advancements seen when moving from GPT-3 to GPT-4. OpenAI has formed a foundations team to tackle the training data issue, but it remains uncertain whether they will gather sufficient data in time for the model’s launch.

    Broader Industry Trends

    OpenAI isn’t alone in experiencing minimal performance improvements. Other companies like Anthropic and Mistral are also witnessing only slight advancements with each new release. One proposed strategy for boosting performance is to continue training the model after its initial release through fine-tuning, although this is merely a temporary fix rather than a sustainable solution.

    Gadgets360, The Information

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  • Google Gemini Standalone App Found on App Store

    Google Gemini Standalone App Found on App Store

    Google’s Gemini AI assistant might be getting its own app in the App Store soon. A Reddit user named "lostshenanigans" managed to download the app while in the Philippines and shared some screenshots in a post.

    App Availability Issues

    Other users attempting to download the app on iOS faced a message saying, "The app is currently not available in your country or region." This new app lets users add Gemini to their home screen for quicker access. Right now, Google only offers Gemini through its main Google app, which means users have to manually switch to the assistant by clicking on a special tab.

    Features of the Gemini App

    According to a report by Google9to5, the listing for the app in the Philippines also mentions a feature called Gemini Live. This feature allows users to have voice conversations with the assistant. Users can ask it to retrieve relevant information from connected services or apps. For instance, you can request it to show meeting details from an email in your account. This functionality isn’t available in the Google app and would need a standalone Gemini app for Android users.

    Recent Integrations

    Recently, Google has added Gemini to Maps, Earth, and Waze, introducing new tools for urban planning, Smart Search with contextual results, enhanced route exploration, and more.

    9to5Google reported this update on Reddit.

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  • Anthropic’s Claude 3.5 Enhancements and Palantir Partnership

    Anthropic’s Claude 3.5 Enhancements and Palantir Partnership

    Anthropic has launched updated versions of Claude 3.5, showcasing enhanced features compared to earlier Claude models and rival AI systems. A collaboration with Palantir allows the Claude AI to be utilized for US government intelligence and defense tasks, with accreditation for handling SECRET-level documents.

    Enhanced Capabilities

    The Claude 3.5 Sonnet comes with significant upgrades, including the ability to interact with computers directly. This means the AI can manage tasks like moving the mouse, launching applications, engaging with windows, and using software tools similarly to a human. In tests conducted against the OSWorld benchmark for open-ended tasks, this new capability achieved a score of 14.9%, nearly double that of competing AIs, though it still falls short of human performance at 72.36%. This gap in performance can be attributed to the AI’s limited experience in learning to operate computers, which makes it difficult to train Claude to perform tasks such as updating spreadsheets with data from multiple files.

    A Faster Alternative

    In addition, a more rapid and compact version named Claude 3.5 Haiku has been introduced, which does not include the computer use features. This AI is optimized for quick responses, avoiding the lengthy processing times seen in other models, while utilizing significantly less computational resources. This efficiency leads to lower costs when handling simpler inquiries. When compared directly with the OpenAI GPT-4o, another mini AI competitor, Haiku consistently outperforms.

    Government Collaboration

    Anthropic and Palantir have unveiled siloed-Claude AI in association with Amazon Web Services (AWS) for classified document usage by the US government. The Department of Defense (DoD) has accredited this IL6 service to aid US agencies in speeding up complex task completion and reducing the workload on human personnel, particularly in areas like identifying and targeting crucial objectives while safeguarding the nation.

    Moreover, alongside Claude applications for Android and Apple devices, Anthropic has rolled out beta versions of Claude for Windows and Mac desktop computers. For those who have more routine needs for AI, users can experiment with the Plaud AI voice recorder (available on Amazon) to automatically transcribe and summarize lengthy meetings that can feel tedious.

    Anthropic news release

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  • Apple and Foxconn Team Up for Custom AI Servers in Taiwan

    Apple and Foxconn Team Up for Custom AI Servers in Taiwan

    Apple is teaming up with Foxconn and LCFC, a Lenovo subsidiary, to create its own AI servers powered by Apple Silicon in Taiwan. This strategy is designed to enhance Apple’s data center capabilities for their upcoming Apple Intelligence services and reduce their dependency on Chinese manufacturers.

    The Reason for Choosing Taiwan

    Sources suggest that Apple chose Taiwan primarily to benefit from Foxconn’s extensive expertise in constructing AI servers. Foxconn is already producing servers equipped with Nvidia’s H100 and H200 GPUs and is preparing to collaborate on new Blackwell-based chips.

    Focus on AI Inference Management

    Unlike its rivals such as Amazon, Google, and Microsoft, Apple’s server strategy focuses more on managing AI inference instead of developing large language models. These servers are intended for internal operations, indicating that production volumes will be lower compared to typical data center configurations.

    Collaboration and Design Support

    This partnership goes beyond just server production; it also involves engineering and design assistance from Foxconn and LCFC. Although Apple may not have a lot of experience in designing data center servers, the development is expected to progress rapidly since these servers are less complex than Nvidia’s GB200 systems.

    Foxconn has AI research facilities in Hsinchu, Taiwan, and San Jose, California, where they are currently collaborating with Nvidia on upcoming GB300 server initiatives. Moreover, additional manufacturing partners like Universal Scientific Industrial may also join to further diversify the production process.

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  • Bees Halt Meta’s Plan for First Nuclear-Powered AI Data Center

    Bees Halt Meta’s Plan for First Nuclear-Powered AI Data Center

    Meta has had to abandon its ambitions for a nuclear-powered AI data center in the United States due to environmental hurdles. The company initially aimed to establish a facility that would utilize emissions-free energy from a recognized nuclear plant operator, positioning Meta as one of the pioneering tech entities to look into nuclear energy specifically for AI processing.

    Environmental Challenges Arise

    Unfortunately, the discovery of a rare bee species on the selected location for the data center introduced regulatory and environmental challenges, which ultimately resulted in the cessation of the project. This unexpected finding presented significant issues that Meta could not navigate, leading to the decision to halt the initiative.

    The Quest for Sustainable Energy

    Big tech firms are increasingly turning to nuclear power as a solution for their energy needs in AI advancement, primarily because AI models necessitate immense computational capabilities, resulting in high energy consumption, often 24/7. Conventional energy sources, particularly fossil fuels, face difficulties in offering sustainable and scalable energy without boosting carbon emissions.

    In contrast, nuclear energy provides a reliable, emissions-free power source that aligns with the environmental goals and long-term objectives of the tech industry, making it an attractive option for companies like Meta.

    A Setback for Meta’s Nuclear Goals

    During an all-hands meeting, CEO Mark Zuckerberg shared his frustration, indicating that the company was ready to proceed with the nuclear supplier to guarantee clean energy for the facility. Although Meta’s nuclear aspirations for this particular site are currently on hold, the company is still considering other pathways to obtain low-carbon energy. This strategy is in line with a larger movement among tech giants such as Microsoft, Google, and Amazon, all of which have recently expressed interest in nuclear energy for their data centers.

    For instance, Microsoft has entered into a 20-year contract to obtain energy from the historic Three Mile Island nuclear facility, which has been renamed the Crane Clean Energy Center, to fuel its own AI projects. Meanwhile, Google and Amazon are investing in small modular reactors (SMRs), which are compact nuclear units designed for safer and more flexible implementation, with Google anticipating that its reactors will be active by 2030.

    Looking Ahead

    Meta is still dedicated to investigating further clean energy sources to support its data-heavy AI operations. The tech industry’s growing dependence on nuclear energy highlights the increasing energy demands of AI and the essential role of clean energy in achieving sustainability objectives. Nevertheless, for the time being, the presence of at-risk wildlife and the regulatory environment have shifted Meta’s plans for a nuclear-driven AI future.

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