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Pymnts
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Napster Owner Infinite Reality Valued at $15 Billion After Acquiring Touchcast
- Metaverse company Infinite Reality has been valued at $15.5 billion after acquiring AI firm Touchcast.
- The $500 million deal marks Infinite Reality's third acquisition this year, as it aims to establish itself as a key player in AI and eCommerce.
- Touchcast's technology allows for convincingly duplicating someone's speech, potentially enabling the creation of digital doppelgangers for presentations.
- According to recent research, over 90% of surveyed retailers have integrated AI into their transaction data workflows for improved analytics capabilities.
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Tech Radar
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Claude tipped to get its answer to ChatGPT’s Advanced Voice Mode soon - is adding an AI voice to a chatbot yet another tick box exercise?
- Anthropic's Claude AI chatbot is set to be upgraded with a new voice mode, as the company looks to catch up with ChatGPT and Gemini.
- The voice mode, named 'Claude voice mode,' is expected to launch this month and will initially offer three diverse voices.
- Other competitors in the AI chatbot space, such as ChatGPT and Gemini, already offer their own voice modes, making the user experience more conversational and natural.
- However, the addition of a voice mode to Claude's AI chatbot is seen as another tick-box exercise in an industry where similar features are rapidly released by competing companies.
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TechCrunch
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Less than a month left to claim your brand’s spotlight at TechCrunch Sessions: AI with an exhibit table
- The deadline to reserve an exhibit table at TechCrunch Sessions: AI is approaching.
- Over 1,200 AI leaders, VCs, and visionaries will be attending the event at UC Berkeley.
- Exhibiting at the event can help build brand credibility and connect with potential clients and collaborators.
- The deadline to reserve a table is on May 9 at 11:59 p.m. PT.
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Medium
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Unlock the Hacker Within: Ethically Transform Your Phone into a Cyber Powerhouse
- Your Android device can be transformed into an ethical hacking lab with the right tools and setup.
- Android phones are recommended due to their open-source nature and deeper customization options.
- Installing a terminal emulator like Termux or JuiceSSH is necessary to run hacking tools.
- Rooting your phone, though optional, provides full administrative access and advanced tool capabilities.
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Medium
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Why 1 + 1 Might Not Equal 2
- Structured Paradox Computation challenges the assumption that 1 + 1 always equals 2.
- In relational systems, like consciousness and identity, '1' is contextual and not a fixed unit.
- SPC models relational collapse, where '1 + 1' may converge into a paradox field.
- The significance of this concept is that AI evolves by encountering contradictions and realizing that '1 + 1' is convergence, not accumulation.
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Geeky-Gadgets
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Boost Productivity with Claude AI and n8n Model Context Protocol (MCP)
- Integrating Claude AI with n8n’s Model Context Protocol (MCP) server tools enables enhanced task management and workflow automation.
- AI-driven interfaces allow for seamless communication and control of various platforms via natural language commands.
- The integration with n8n’s MCP tools further strengthens the functionality, enabling efficient task execution with simplified interactions.
- The setup process involves configuring n8n’s MCP servers and client nodes to establish secure connections and ensure accurate task execution.
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Medium
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How AI Like ChatGPT and Gemini Are Turning Your Smartphone Into a Genius
- Flagship smartphones like Google Pixel 8, Samsung Galaxy S24, and iPhone 15 are integrating AI at hardware and software levels.
- Gemini and ChatGPT integration enables more advanced voice commands and intuitive assistance on smartphones.
- Smartphone cameras are transforming into professional-grade tools through on-device AI processing.
- AI models will lead to even deeper integration, potentially with AI agents managing digital lives autonomously.
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Silicon
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ASML, Others Outline Impact Of Trump’s Tariffs
- ASML Holdings, the world’s largest chip-making equipment supplier, warns that recent tariff announcements have increased uncertainty in the macro environment.
- US semiconductor equipment makers, including Applied Materials, Lam Research, and KLA, could face a yearly loss of around $350 million due to the tariffs.
- ASML announces its Q1 financial results, with a net profit of 2.33bn euros and revenues of 7.7bn euros.
- ASML's CFO states that the company is ready to pass most of the tariff costs onto customers and believes that the burden of tariffs should be allocated in a fair way.
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Siliconangle
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Image Credit: Siliconangle
The future of private 5G: How Kyndryl and Nokia are shaping the digital transformation of critical infrastructure
- Private 5G networks are revolutionizing industrial operations and critical infrastructure, enabling real-time connectivity and scalability.
- Kyndryl and Nokia are collaborating to enhance worker safety, operational efficiency, and scalability for global enterprises.
- The partnership focuses on bridging connectivity and security, offering end-to-end solutions integrating AI, edge computing, and safety applications.
- Private 5G's role in real-time data integration and AI deployment is transforming industrial operations for improved efficiency and worker safety.
- Nokia's expertise in private wireless networks complements Kyndryl's services in systems integration, delivering tailored solutions for enterprises.
- The deployment of private 5G networks extends to various sectors like oil and gas, mining, and manufacturing, emphasizing secure, real-time data communication.
- Edge computing and far-edge strategies reduce latency, enabling near-real-time data processing essential for mission-critical tasks.
- AI adoption at the far edge enhances decision-making speed and reliability in critical infrastructure environments.
- Kyndryl and Nokia emphasize the importance of security and compliance in navigating regulatory landscapes for private 5G deployments.
- Private 5G and edge computing are reshaping industries by providing secure, scalable solutions infused with AI and operational intelligence.
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Medium
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Image Credit: Medium
From Next-Gen Weather to Calm Tech to Shopping in the Google Zero Era: The Second Coming of…
- The consumer 'technology window' that produced giants like Facebook, Twitter, and Uber closed around 2014, leading to a shift favoring B2B unicorns over B2C companies by 2023.
- In 2025, indications suggest a correction in the imbalance towards consumer startups given the maturity for disruption in the existing ecosystem.
- Emerging consumer tech includes Oriux's hyper-localized weather service, hinting at a wave of innovation in consumer apps.
- AI is expected to birth new revenue-generating companies, both B2C and B2B, indicating a favorable time for consumer tech innovation.
- Market indicators signal a potential shift towards consumer tech, driven by changing demographics and resilient consumer spending, challenging the dominance of enterprise-focused investments.
- Cal AI, developed by teenagers, exemplifies the success potential in consumer apps using large language models (LLMs) and AI technology.
- European VCs are urged to reevaluate their caution towards consumer tech investments as lower valuations and AI advancements offer growth opportunities in the sector.
- AI-driven consumer tech innovations like personalized shopping assistants, circular economy platforms, and AI-enabled discovery in product offerings are showing promise in the market.
- Consumer tech renaissance is expected to create new markets through AI democratization, offering significant opportunities for value creation in the industry.
- The evolving consumer tech landscape emphasizes the importance of network effects, cultural alignment, speed in execution, and integration of AI capabilities for success.
- Investors and founders are urged to capitalize on the emerging window of opportunity in consumer tech, leveraging AI and adopting growth-oriented strategies for future success.
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Medium
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The State of EU Green AI
- EU is investing heavily in AI infrastructure, with projects like AI Factories and a €200 billion investment in AI.
- The EU aims to make AI industry-specific and productive with a focus on science and tech mastery.
- AI requires specific bulky hardware and has a unique supply chain that includes carbon impact and environmental considerations.
- The EU is promoting AI hardware development and energy-efficiency standards to tackle AI's carbon footprint.
- Data center operations, model training, and end-of-life management are key focus areas for decarbonizing AI in the EU.
- Initiatives like the AI Innovation Package and EuroHPC provide resources for startups to access supercomputing and support model training.
- The EU is mobilizing significant funds for AI investments, including building data centers, gigafactories, and promoting sustainable practices.
- Corporate investments from tech giants like Microsoft and Amazon are also contributing to the development of AI infrastructure.
- Global efforts in AI, particularly in China, are driving significant investments in AI applications and technologies.
- The EU, along with global players, is focused on inclusive and sustainable AI development to lead in the race for Green AI.
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Embedded
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Should You Use AI to Develop Embedded Systems?
- Developers often hesitate to use AI for developing embedded systems due to concerns like lack of understanding of hardware constraints, errors, and data privacy issues.
- However, AI can still be beneficial in speeding up and reducing costs in embedded systems development.
- AI-generated code for tasks like GPIO driver creation can provide a good starting point and save time.
- Although AI may make mistakes, it can be a helpful assistant when provided with the right context and guidance.
- Treating AI as a programming partner and being clear and specific when using it can lead to better outcomes.
- Data privacy and ownership concerns arise when using AI for generating code, especially related to licensing and intellectual property.
- AI can be effectively utilized for tasks like generating boilerplate code, improving workflows, and automating routine activities in embedded systems development.
- Despite the potential risks, exploring AI applications in developing embedded systems can lead to enhanced efficiency and innovation.
- The key is to identify safe and strategic areas where AI can be integrated to optimize embedded system development processes.
- Overall, leveraging AI in embedded systems development can offer numerous benefits if utilized thoughtfully and ethically.
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Medium
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Image Credit: Medium
The Ultimate Guide to Choosing the Best Machine Learning Algorithm
- Choosing the best machine learning algorithm is crucial for successful data-driven projects.
- Understanding the basics of machine learning and the problem at hand is essential for algorithm selection.
- Considerations such as data type, dataset size, and problem type (classification, regression, or clustering) play a vital role in algorithm selection.
- The right algorithm can transform raw data into actionable insights, providing accuracy and clarity.
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Medium
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Image Credit: Medium
New Image Generation Transforms Business Strategy and Creative Intelligence
- The introduction of image generation within GPT-4o marks a pivotal shift in visual creativity.
- This development democratizes visual creation tools for business users of all sizes.
- GPT-4o's autoregressive method allows precise rendering of complex scenes with 15-20 distinct objects.
- It represents a significant advancement in text and AI image generation models.
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TechnologyReview
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Image Credit: TechnologyReview
Adapting for AI’s reasoning era
- Advanced reasoning models in AI are evolving, allowing for nuanced decision-making and multi-step problem-solving, marking a shift from rote regurgitation to genuine reasoning.
- Reasoning models explore hypotheses, adjust approaches based on training data, and create decision trees to find optimal solutions, requiring extended computation time in newer models for complex problem-solving.
- Reasoning-capable AI has vast applications in enterprises, such as supporting diagnostic decisions in healthcare, accelerating scientific discoveries, aiding financial analysis, and offering autonomous planning capabilities.
- However, deploying reasoning models requires robust infrastructure, collaborative efforts between providers and hardware manufacturers, and governance frameworks to ensure safe and effective use, especially in high-stakes contexts like autonomous vehicles.
- Microsoft's collaboration with NVIDIA focuses on creating a holistic system architecture to handle diverse AI demands, allowing companies to leverage reasoning models without managing underlying complexities and keeping pace with technological advancements.
- Advancements in AI infrastructure tailored for reasoning and agentic models are crucial for making reasoning-capable AI accessible to a broader range of organizations, facilitating progress in scientific discoveries and societal advancements.
- The future evolution of reasoning-capable AI systems holds the promise of powering scientific research and breakthroughs that could significantly impact humanity's progress, driving innovation and potentially leading to groundbreaking discoveries.
- Collaborations such as Microsoft and NVIDIA's accelerate AI development and performance, ensuring companies can harness the power of reasoning models without being burdened by intricate technicalities, advancing the field of AI at a rapid pace.
- The evolution towards reasoning-capable AI reflects a transition towards more sophisticated problem-solving and decision-making processes, with the potential to revolutionize various industries and drive significant advancements in technology and society.
- Reasoning models necessitate increased computational resources, posing scaling challenges that require innovative solutions and strategic partnerships to address, facilitating the widespread adoption of advanced AI capabilities in organizations.
- As reasoning-capable AI systems continue to develop, the focus on enhancing infrastructure and collaboration between key players in the industry remains essential for unlocking the full potential of AI technology and driving impactful outcomes across diverse sectors.
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