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Hedera introduces a new AI solution with Accenture and EQTY Labs
Hedera Foundation is collaborating with Accenture and EQTY Lab to launch a new artificial intelligence solution aimed at bringing verifiable AI governance to the public sector. HBAR , the native token of Hedera, remained largely flat despite the news as it traded around $0.18. The token’s value is up 0.5% in the past 24 hours and 6% in the last seven days. Hedera Foundation joins forces with Accenture and EQTY Lab Announced today, this initiative leverages the Hedera network’s advanced distributed ledger technology (DLT) to ensure transparency, auditability, and trust in autonomous AI systems, addressing critical needs in public sector operations. Hedera Foundation @HederaFndn · Follow We’re excited to introduce a new AI solution with @Accenture and @EQTYLab that will help governments and public sector organizations manage AI-driven decisions with transparency, auditability, and trust via the @Hedera network 🤝 Watch on Twitter View replies 4:04 pm · 11 Jun 2025 410 Reply Copy link Read 19 replies The new solution integrates EQTY Lab’s AI Integrity Suite with Hedera’s Consensus Service (HCS) and Token Service (HTS), creating an immutable record of AI decisions and actions. The Hedera Token Service (HTS) is a core feature of the Hedera network, a high-performance, enterprise-grade distributed ledger technology (DLT) platform. HTS enables users to create, manage, and transact with native digital tokens on Hedera in a secure, scalable, and cost-effective manner. This framework enables public sector entities to track and verify AI processes, ensuring compliance with evolving regulations like the EU AI Act and NIST standards. By anchoring AI workflows in Hedera’s secure, scalable network, the solution provides a tamper-proof audit trail, fostering accountability and public trust in AI applications. What does this mean? Accenture, a leading player in AI, will develop playbooks to guide the implementation of this solution at scale. These resources will outline business logic for AI deployment and strategies to maximize Hedera’s capabilities, particularly in areas like regulatory compliance and data integrity. “Public sector clients are enthusiastically embracing continuous reinvention through the adoption of AI and agentic solutions to achieve scaled impact. This shift brings with it a heightened demand for oversight, accountability and reliability. The integration of these technologies not only enhances runtime governance, but also positions the Hedera network as a crucial platform,”said Bryan Rich, Senior Managing Director of Global AI for Public Sector at Accenture. Hedera is a blockchain platform whose network has a governing council that includes global giants such as Google, HITACHI, Dell Technologies, Deutsche Telekom, and IBM. It also features crypto-focused players such as BitGo and Chainlink. The Hedera network offers high-throughput, low-cost transactions with instant finality, making it ideal for enterprise-grade AI governance. In a comment about the integration with Accenture and EQTY Lab, Heder’s chief operating officer, Shyam Nagaraja,n stated: “This partnership positions Hedera as a leader in AI governance, enabling secure and compliant AI adoption in the public sector.” Hedera’s move comes amid growing traction for AI, including for governments. AI’s rapid rise is thus key to this integration with Accenture and EQTY Lab. Tapping into Hedera’s distributed ledger technology means a new standard for responsible AI use. The post Hedera introduces a new AI solution with Accenture and EQTY Labs appeared first on Invezz

Invezz 2025-06-11 19:07
OpenAI Open Model: Strategic Delay Hints at Amazing AI Breakthrough
BitcoinWorld OpenAI Open Model: Strategic Delay Hints at Amazing AI Breakthrough For those tracking the rapid evolution of artificial intelligence and its potential impact across technology sectors, including cryptocurrency and blockchain, news from OpenAI is always significant. The highly anticipated release of OpenAI’s first open model in years has hit a snag, with the OpenAI open model now expected later this summer instead of June. Why the AI Model Delay? Sam Altman Explains The announcement came directly from OpenAI CEO Sam Altman AI , who shared the update on X. Altman stated, “We are going to take a little more time with our open-weights model, i.e. expect it later this summer but not June.” This indicates a shift from the previously targeted early summer window. The reason provided for the AI model delay is particularly intriguing. Altman hinted at a significant development within the research team, describing it as “unexpected and quite amazing.” He believes this breakthrough will make the additional waiting time worthwhile, suggesting substantial improvements or new capabilities are being integrated into the model. What Are OpenAI’s Goals for This Open Model? OpenAI has ambitious plans for this forthcoming model. It is slated to possess reasoning capabilities comparable to their proprietary ‘o-series’ models. A primary objective is for the OpenAI open model to set a new standard and outperform existing open reasoning models currently available, such as DeepSeek’s R1. The company aims to push the boundaries of what’s possible with open-source AI, providing developers and researchers with a powerful tool that can handle complex tasks and exhibit advanced reasoning skills. This move is seen by many as an effort to re-engage with the open-source community after years focused primarily on closed models. How Does the Competitive Landscape Look for OpenAI’s Release Date? Since OpenAI first signaled its intention to release an open model, the competitive landscape in the AI space has intensified significantly. Other labs have not stood still, releasing their own advanced models, making the timing of the OpenAI release date even more critical. For example, Mistral, known for frequently releasing open models, recently launched its first family of AI reasoning models called Magistral. Similarly, the Chinese AI lab Qwen introduced a family of hybrid AI reasoning models capable of switching between deliberate, time-consuming reasoning and faster, traditional responses. These developments highlight the pressure on OpenAI to deliver a truly competitive offering when its model finally arrives. Potential Features and OpenAI’s Relationship with Open Source Beyond core performance benchmarks, OpenAI has reportedly considered integrating complex features to make its open model stand out among competitive AI models . Discussions have included enabling the open model to connect with OpenAI’s cloud-hosted AI models for tackling particularly complex queries. While it remains uncertain which of these advanced features will make it into the final release, their consideration underscores the effort to build a top-tier open model. The release holds considerable importance for OpenAI’s standing with researchers and developers globally. Sam Altman AI has previously acknowledged that OpenAI landed on the “wrong side of history” regarding open-sourcing its models. Releasing a powerful, competitive open model is crucial for rebuilding trust and fostering stronger relationships within the AI community. Conclusion: Waiting for the Breakthrough The delay in the OpenAI release date for its highly anticipated open model is certainly a pause, but the reason cited – an “unexpected and quite amazing” research discovery – suggests that the wait may be justified. As the field of competitive AI models continues to evolve rapidly, the pressure is on OpenAI to deliver a model that not only meets but exceeds expectations. The coming months will reveal whether this strategic delay leads to a breakthrough that significantly impacts the open AI landscape. To learn more about the latest AI model trends, explore our articles on key developments shaping AI models features. This post OpenAI Open Model: Strategic Delay Hints at Amazing AI Breakthrough first appeared on BitcoinWorld and is written by Editorial Team

Bitcoin World 2025-06-11 18:10
Apple AI Stumbles: Benchmarks Reveal Underperformance
BitcoinWorld Apple AI Stumbles: Benchmarks Reveal Underperformance In the fast-evolving world of technology, where advancements often ripple across markets, including the digital asset space, news from major players like Apple is always significant. Recently, Apple announced updates to the Apple Intelligence features powered by its latest AI models. However, internal company benchmarks reveal a surprising reality: these new models appear to underperform compared to established rivals, raising questions about Apple’s position in the intense Generative AI race. Decoding Apple AI Benchmarks Apple shared insights into the performance of its updated AI models through a blog post. The results, based on human evaluations, painted a picture that wasn’t quite as dominant as one might expect from the tech giant. Apple On-Device Model: This model runs locally on devices like the iPhone. Apple stated that human testers rated its text generation quality as “comparably” good to, but not better than, text from similarly sized models from Google and Alibaba. This model is roughly 3 billion parameters in size. Apple Server Model: This more powerful model operates in Apple’s data centers. Testers rated its performance behind OpenAI’s GPT-4o, a model that has been available for over a year. Image Analysis: In tests evaluating image understanding, human raters preferred Meta’s Llama 4 Scout model over the Apple Server model. This is notable because Llama 4 Scout has, in other tests, performed worse than leading models from companies like Google, Anthropic, and OpenAI. These AI benchmarks suggest that while Apple is making progress, it may still be playing catch-up in certain areas of Generative AI development. What Do These AI Benchmarks Mean? The benchmark results lend support to earlier reports suggesting that Apple’s AI research efforts have faced challenges in keeping pace with competitors. Apple’s AI capabilities have sometimes been perceived as less advanced in recent years, and a significant planned upgrade to its voice assistant, Siri, has reportedly been delayed indefinitely. The company has even faced lawsuits from customers alleging that it marketed AI features that were not yet delivered. While the benchmarks show areas where Apple’s models lag, it’s important to note the capabilities Apple highlights for its new Apple AI models: Apple On-Device: Powers features like summarization and text analysis. Both Models: Boast improved tool-use and efficiency compared to their predecessors. Language Support: Can understand around 15 languages. Training Data: Benefited from an expanded dataset including images, PDFs, documents, manuscripts, infographics, tables, and charts. Accessing Apple AI Models for Developers For developers, access to these new capabilities is opening up. As of a recent announcement, third-party developers can utilize the Apple On-Device model via Apple’s Foundation Models framework. This allows integration of features like summarization and text analysis into third-party applications, potentially enabling new functionalities within the Apple ecosystem. The Challenge Ahead in Generative AI The field of Generative AI is intensely competitive, with rapid advancements happening across the industry. Companies are investing heavily in research, development, and infrastructure to build ever more capable AI Models. Apple’s benchmark results underscore the significant challenge involved in not just developing advanced AI but also in surpassing the performance of models already in the market from dedicated AI labs and tech rivals. While Apple has a strong ecosystem and user base, success in Apple Intelligence will ultimately depend on the perceived quality and utility of its AI features, which are directly tied to the performance of its underlying AI models. The path to leading the Generative AI race appears to require substantial continued effort and innovation for Apple. Summary: A Reality Check for Apple AI Apple’s latest AI benchmarks present a candid view of its progress in artificial intelligence. While the company is integrating AI deeply into its operating systems and offering developer access, its new AI models are currently performing comparably to or behind older models from competitors like OpenAI, Google, Alibaba, and Meta in key tests. This highlights the significant hurdles Apple faces in catching up in the competitive Generative AI landscape and delivering on the full promise of Apple Intelligence features. To learn more about the latest AI market trends , explore our article on key developments shaping AI Models and their impact on the future digital economy. This post Apple AI Stumbles: Benchmarks Reveal Underperformance first appeared on BitcoinWorld and is written by Editorial Team

Bitcoin World 2025-06-11 16:40

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