Blog – Next 2 GenAI

25 October 2024 Artificial Intelligence, Technology n2ginnovate

2024: The Era of Generative AI for Indian IT

According to industry analysts, 2024 is set to be the year when generative AI takes center stage in the Indian IT sector. Nearly 50% of the deals this year are expected to be driven by generative AI, contributing around 2% to the industry’s total revenue. Leading the AI charge are top IT giants like Infosys, […]

5 October 2024 Technology n2ginnovate

TCS Wins AI Office Deals Worth $10M–$30M

Tata Consultancy Services (TCS) is making significant strides in the AI landscape, securing contracts to set up AI offices for clients with deal sizes between $10 million and $30 million. During a recent Q2 earnings call, CEO K Krithivasan shared that while many generative AI (GenAI) engagements start small, TCS is also winning larger, long-term […]

4 October 2024 Technology n2ginnovate

The Race for LLM Inference Dominance Accelerates

The race for inference performance and training is reaching new heights, with companies like SambaNova, Cerebras, and Groq breaking records for token speed, especially with Meta’s Llama. Meanwhile, OpenAI is taking a different approach by deliberately slowing down inference to enhance “thinking” capabilities, allocating more compute resources to reasoning and integrating with external tools for […]

2 July 2024 Technology n2ginnovate

IBM Unveils Granite 3.0 LLMs for Enterprise-Grade AI Solutions

IBM has launched Granite 3.0, the latest version of its large language models (LLMs) tailored for enterprise use, blending high performance with cost-efficiency. These models, built with over 12 trillion tokens, support 12 natural languages and 116 programming languages, making them ideal for diverse industries like cybersecurity and text generation. Granite 3.0’s versatility allows businesses […]

3 January 2024 Artificial Intelligence, Robots n2ginnovate

Claude 3.5 Sonnet Enables AI Automation

Anthropic has introduced a new capability called “computer use” for its Claude 3.5 Sonnet language model, allowing it to operate computers like a human. This feature, currently in beta, enables Claude to perform tasks such as typing, clicking, and navigating software, paving the way for advancements in robotic process automation (RPA). By leveraging the new […]

1 October 2023 Technology n2ginnovate

Can Large Language Models (LLMs) Truly Follow Instructions?

Large Language Models (LLMs) like GPT-4, Claude, and Gemini are making a big impact in areas like education, healthcare, and customer service. These AI models are designed to understand, generate, and respond to human language, enabling tasks such as content creation, answering questions, and providing mental health support. However, their true value lies in how […]

3 January 2023 Artificial Intelligence n2ginnovate

Protect AI Secures $60M to Lead the Charge in Responsible AI Security

Protect AI has raised $60M in Series B funding, propelling the company to new heights in securing AI and machine learning (ML) systems from unique vulnerabilities and emerging threats. The latest round, led by Evolution Equity Partners, along with participation from prominent investors such as 01 Advisors, StepStone Group, and Samsung, increases the company’s total […]

2 January 2023 Artificial Intelligence n2ginnovate

LLMs Enhance Hospital Quality Measure Reporting

Recent research published in New England Journal of Medicine AI shows that large language models (LLMs) can accurately process hospital quality measures, aligning with manual reporting in 90% of cases. The pilot study used an LLM system to analyze Severe Sepsis and Septic Shock Management Bundle (SEP-1) measures at UC San Diego Health, demonstrating significant […]

1 January 2023 Artificial Intelligence, Technology n2ginnovate

Are Large Language Models (LLMs) Ready for Healthcare?

LLMs like GPT-4 are making waves in medicine, with potential to save time and reduce burnout. Yet, their adoption in clinical settings faces serious hurdles. Mistakes, known as hallucinations, are common. For example, Dr. Ravi Parikh noted LLMs misinterpreting test results, which he had to manually correct. Such errors can burden physicians rather than alleviate […]

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