Large language models (LLMs) are the backbone of generative AI technologies, such as ChatGPT and Google Gemini. These models don’t comprehend language like humans; instead, they use vast amounts of training data to predict word sequences based on patterns. LLMs have millions or billions of parameters and rely on deep learning, akin to teaching a child through examples. They process text by breaking it into tokens and creating a map of word relationships, refining their predictions through continuous feedback. Despite their abilities, LLMs have weaknesses: they can fabricate information, struggle with unique queries or abstract reasoning, and often lack current knowledge. Integrating LLMs with search engines aims to improve the accuracy of responses, though it presents challenges like potential misinformation. Understanding how LLMs operate is essential for navigating their capabilities and limitations in our increasingly AI-driven world.
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Understanding the Distinction: What You Need to Know About LLMs, AI, and the Technology Behind Chatbots
AI Insights | VentureBeat News
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“Akamai Discusses the Powerful Potential and Challenges of AI”
Akamai’s Israel HR Director, Sivan Baron, emphasizes the company’s view of AI as a productivity enhancer rather than a replacement for human labor. As part of the “HR in the AI Era” series, Baron discusses Akamai’s commitment to AI, which influences its overall business strategy in product enhancement, customer and employee experience, and security against AI threats. Although AI is used in HR through tools such as a new cloud-based HR solution and evaluation mechanisms for candidates, the company is cautious about its deployment, focusing on potential challenges like inclusion. Baron also notes ongoing workforce challenges due to global economic and geopolitical factors and emphasizes the resilience of employees amidst these pressures. Akamai remains committed to growth, with expectations to continue expanding its global headcount and integrating AI into various operational facets, reinforcing its position in cyber security and cloud computing.
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AIIMS-P to Enhance Patient Care with AI-Driven Technology | Patna News
AIIMS Patna has partnered with the health ministry’s e-health division to develop AI-driven healthcare solutions and has acquired AI-enabled medical devices to improve patient treatment. Dr. Sanjiv Kumar, head of cardiothoracic surgery, emphasized the importance of understanding AI’s principles as it transforms healthcare through enhanced diagnostics, such as detecting cancers and heart diseases from medical imaging. The orthopaedic department has started robotic surgeries for higher precision. To combat tuberculosis (TB), the state health department plans to implement AI-assisted screenings in rural areas with portable X-ray machines, aiming to identify the approximately 200,000 TB patients in Bihar and streamline their treatment. Pramod Kumar Singh, the director of disease control, noted that AI technology could improve TB detection and treatment protocols. Dr. Satish Kumar of Nalanda Medical College urged for AI equipment in all state health centers to facilitate timely diagnoses and reduce hospital overcrowding.
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The Growing Adoption of AI: Company Insights for 2025
The adoption of artificial intelligence (AI) in business has surged, particularly with generative AI technologies like large language models (LLMs). Currently, 78% of global companies utilize AI, with 82% either implementing or exploring its use. Notably, 71% have applied generative AI in various functions. The global AI market is expected to reach $1.85 trillion by 2030. India leads in AI adoption, with 59% of companies using it, while the U.S. lags at only 33%. Major business sectors leveraging AI include customer service (56%), cybersecurity (51%), and digital assistants (47%). Larger enterprises are significantly more likely to adopt AI than smaller firms, with over 50% of businesses with more than 5,000 employees utilizing AI. As AI adoption expands, businesses increasingly invest in AI tools and technology, aiming for enhanced efficiency and cost savings. The trend shows a promising future for AI roles, with many companies actively hiring for AI-related positions.
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Transforming Education: The Impact of AI Agents and Innovations Like Kira Learning
Today’s classrooms are experiencing rapid transformation due to Artificial Intelligence (AI), which is revolutionizing teaching and learning. AI agents like Kira Learning facilitate personalized support for students and streamline educators’ tasks by automating grading and lesson planning. Kira Learning stands out by using advanced AI to adapt lessons in real-time based on individual student performance, freeing teachers from administrative burdens while enhancing classroom engagement. Other platforms, such as Squirrel AI, also provide personalized learning but Kira offers a comprehensive solution across various educational needs. Additionally, AI technologies, including VR and gamification, further engage students in the learning process. However, challenges such as ensuring equitable access to AI tools, safeguarding data privacy, and mitigating bias must be addressed. Overall, while AI capabilities have the potential to enhance personalization, efficiency, and engagement in education, it is essential that these systems assist rather than replace the vital role of teachers in fostering student relationships.
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Unlocking Gemini AI on Your Google TV: A Guide for When It Launches
In 2017, Google Assistant debuted on smart TVs, but it has since been replaced by the Gemini assistant, which is set to arrive on TVs later this year after being integrated into smartphones and desktops. At the I/O 2025 event, Google revealed that Gemini will function similarly to its predecessor, allowing users to invoke it with the “hey Google” hotword through a remote’s mic or the TV’s microphone array. Brands like TCL are developing Google TVs with far-field microphones for seamless interaction. Gemini enhances user experience with advanced conversational abilities, enabling users to ask for movie recommendations or sports updates easily. Google showcased a vision for next-gen smart TVs featuring onboard mics and ambient sensors that respond to user presence by displaying customized content. Models from TCL, Hisense, and Sony will support Gemini, with more brands expected to follow, aiming for improved content discovery and engagement.
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Revolutionizing Peripheral Artery Disease Education: A Showdown Between ChatGPT and Google Gemini
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Unlocking Custom AI Art: A Guide to Using Midjourney’s Omni Reference
Midjourney’s new Omni Reference feature brings users closer to translating their creative visions into AI-generated visuals. By allowing the upload of reference images—such as photographs or sketches—the tool permits customization like never before. Users can adjust the “omni reference weight” parameter (from 1 to 1,000) to control the extent to which the AI adheres to the uploaded image. While the feature promises flexibility for artistic experimentation, it has limitations, such as image loading errors and inconsistent output quality, with a success rate between 25% and 45%. Additionally, integrating multiple references can be challenging. Effective prompting and understanding weight parameters are crucial for achieving desired results. Despite these hurdles, the Omni Reference feature holds substantial potential across various fields, including design, advertising, and arts education, encouraging users to reimagine the possibilities of AI in creative processes. Ongoing updates from Midjourney could further enhance its functionality and user experience.
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Run AI Models on Your Phone, No Internet Required!
The development offers significant advantages, primarily enhanced privacy and faster performance. By processing everything on the device, it eliminates the need to send data to cloud servers, thereby minimizing the risk of security breaches. This local operation also ensures that AI responses are instantaneous, without waiting for server replies. Additionally, the app utilizes Hugging Face’s open AI models and operates on Google’s AI Edge platform, ensuring optimal performance across various devices. This approach not only boosts efficiency but also strengthens user security, making it a compelling solution for both privacy-conscious users and those seeking quick AI responses.
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