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Posts tagged with LLM

Mistral AI's Balancing Act

Mistral 7B shocked the AI world with its open source muscle. But will Mistral stay committed to openness as they flex for funding?

Mistral AI's Balancing Act

Mistral AI, a Paris-based startup, has made significant strides in the AI industry by releasing a high-performing 7 billion parameter model under an open-source license. While the company champions the open-source ethos, it also acknowledges the need for commercial products.

Mistral AI | Open source models
Frontier AI in your hands

The Paris-based startup Mistral AI has recently made waves in the AI community by open-sourcing a powerful 7 billion parameter generative language model called Mistral 7B. This model achieved state-of-the-art performance relative to its size, outperforming models like Anthropic's Llama 2 13B on multiple benchmarks.

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The Generative AI Tech Stack Featured Post

Beyond the Hype: A Pragmatic Technical Framework for Understanding and Building Enterprise-Ready Generative AI Systems

The Generative AI Tech Stack

Since the launch of ChatGPT, businesses and enterprises have been exploring ways to implement large language models into their organizations. However, for non-technical stakeholders, it can be challenging to grasp how all the components of generative AI fit together into a cohesive system.

To bridge this gap, this article introduces the Generative AI Tech Stack - a conceptual model for understanding the layers that comprise a complete generative AI solution. By structuring the stack into logical components, we aim to provide executives, managers, and other business leaders an accessible overview of how the parts interconnect.

The Generative AI Tech Stack

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Improving Large Language Models with Retrieval Augmented Generation Featured Post

Redefining AI Conversations: How Retrieval Augmented Generation is supercharging Large Language Models for a smarter future.

Improving Large Language Models with Retrieval Augmented Generation

The Generative AI Revolution: An Introduction to Retrieval Augmented Generation

The release of ChatGPT in November 2022 sparked tremendous excitement about the potential for large language models (LLMs) like it to revolutionize how people and organizations use AI. However, in their default form, these models have limitations around working with custom data.

This is where the idea of retrieval augmented generation (RAG) comes in. RAG is a straightforward technique that enables LLMs to dynamically incorporate external context from databases. By retrieving and appending relevant data to prompts, RAG allows LLMs to produce high-quality outputs personalized to users' needs.

Since ChatGPT

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Video Review: Opportunities in AI by Andrew Ng Featured Post

Forget killer robots - AI's real power is its ability to boost business. - A review of Opportunities in AI speech by Andrew Ng

Video Review: Opportunities in AI by Andrew Ng

I recently watched a video featuring Andrew Ng, a pioneering thought leader in artificial intelligence, as he discussed current trends and future opportunities in AI.

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I don't usually publish my notes but I will make an exception here. If this is a format you find useful let me know we can do this more regularly

As founder of Google Brain and former chief scientist at Baidu, Ng has unique insight into the field. His talk highlighted two significant forces shaping the landscape for AI innovation.

Key Takeaways by Viewpoints

For the average person:

  1. AI will increasingly automate tasks in many
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Generative AI for Legal Professionals - Promise, Peril, and a Path Forward Featured Post

ChatGPT for lawyers - saviour or siren song? Generative AI promises tantalizing efficiency gains but also poses profound perils demanding diligence.

Generative AI for Legal Professionals - Promise, Peril, and a Path Forward

While generative AI tools like ChatGPT offer efficiency gains, their use by legal professionals raises serious concerns about accuracy, confidentiality, and ethics that demand caution and regulatory guidance.

This Article Covers:

Key Challenges and Concerns

  • Ensuring Accuracy and Accountability
  • Confidentiality and Client Trust
  • Staying Current with AI's Rapid Pace of Change
  • The Opacity of AI's "Black Box"
  • The Specter of Algorithmic Bias
  • Cybersecurity Vulnerabilities
  • Navigating Ethical Quandaries

Guidance Emerging for Responsible AI Use

  • Bar Associations Developing Policies and Frameworks
  • Following Developing Best Practices

Strategies for Effective Adoption

  • Mastering Prompt Engineering
  • Rigorous Human Review and Validation
  • Transparent Communication with Clients
  • Evaluating
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