Fine-Tune Your LLMs or Face AI Failure

In this contributed artticle, Dr. Muddu Sudhakar, CEO and Co-founder of Aisera, focuses on the downsides of general-purpose Gen AI platforms and why enterprises can derive more value from a fine-tuned model approach.

Video Highlights: The 3 Steps of LLM Training with Lisa Cohen

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Lisa Cohen, Google’s Director of Data Science and Engineering, to discuss the capabilities of the cutting-edge Gemini Ultra LLM and how it stands toe-to-toe with GPT-4.

Overcoming the Technical and Design Hurdles for Proactive AI Systems

In this contributed article, George Davis, founder and CEO of Frame AI, howlights how we find ourselves at an early, crucial stage in the AI R&D lifecycle. Excitement over AI’s potential is dragging it into commercial development well before reliable engineering practices have been established. Architectural patterns like RAG are essential in moving from theoretical models to deployable solutions.

Video Highlights: A Code-Specialized LLM Will Realize AGI — with Jason Warner

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by poolside co-founder and CEO Jason Warner who sheds light on how code-specialized LLMs could vastly outperform generalized counterparts like GPT-4.

Generative AI Report – 3/1/2024

Welcome to the Generative AI Report round-up feature here on insideBIGDATA with a special focus on all the new applications and integrations tied to generative AI technologies. We’ve been receiving so many cool news items relating to applications and deployments centered on large language models (LLMs), we thought it would be a timely service for readers to start a new channel along these lines. The combination of a LLM, fine tuned on proprietary data equals an AI application, and this is what these innovative companies are creating. The field of AI is accelerating at such fast rate, we want to help our loyal global audience keep pace.

Securing GenAI in the Enterprise

Opaque Systems released a new whitepaper titled “Securing GenAI in the Enterprise.” Enterprises are chomping at the bit to use GenAI to their benefit but they are stuck. Data privacy is the number one factor that stalls GenAI initiatives. Concerns about data leaks, malicious use, and ever-changing regulations loom over the exciting world of Generative AI (GenAI), specifically large language models (LLMs).

Microsoft Expands AI Reach with Partnership with French Start-up Mistral

Microsoft has taken another notable step forward in the realm of artificial intelligence by announcing a strategic partnership with Mistral, a French AI start-up based in Paris. This move further exemplifies Microsoft’s commitment to broaden its presence in the rapidly evolving AI industry beyond its existing alliance with OpenAI and at a global scale.

Video Highlights: How to Integrate Generative AI Into Your Business — with Piotr Grudzień

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Founder of Quickchat AI Piotr Grudzień who believes the key to any successful AI platform is to ensure it can be tailored to a company’s specific needs.

Harnessing the Capabilities of Gen AI for Unprecedented Impact and Effortless Integration

In this contributed article, Ajay Kumar, CEO at SLK Software, discusses how generative AI provides unprecedented impact and effortless integration for the banking, insurance, and manufacturing industries. Ajay elaborates on why you need an adoption framework to successfully implement generative AI, how different categories of generative AI fit into an enterprise adoption framework, and navigating stakeholder challenges of adopting generative AI

Veritas Survey Finds Workers are Putting Businesses at Risk by Oversharing with GenAI Tools

Our friends over at Veritas just released a new survey revealing that workers are oversharing with generative AI tools, putting businesses at risk. Nearly a third (31%) of global office workers admitted to inputting potentially sensitive information into generative AI tools, such as customer details or employee financials.