Best of Generative AI — May 2024
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Community Picks·2y
The State of Data Engineering 2024
The 2024 State of Data Engineering report discusses the influence of GenAI on software infrastructure, the expansion of product offerings due to the economic downturn, and the impact of open table formats and their catalogs in the data lake industry. It also highlights the importance of data version control and observability in AI/ML systems.
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Machine Learning News·2y
Anthropic AI Launches a Prompt Engineering Tool that Generates Production-Ready Prompts in the Anthropic Console
Anthropic AI has launched a prompt engineering tool in the Anthropic Console that generates production-ready prompts, helping users maximize their outputs using generative AI and achieve optimal results.
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Medium·2y
Why AI wont take your job just yet
Generative AI is a branch of artificial intelligence that focuses on creating new data samples. It can be used for tasks such as image generation, text generation, and music composition. Generative AI can be applied in two ways: augmentation, which helps with human tasks, and automation, which fully performs human tasks. While AI can automate simple and repetitive tasks, it cannot replicate the humanity and creativity of human work. AI should be seen as a tool that empowers humans rather than replaces them.
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Pika – Image Generation made easy
Pika offers a subscription for unlocking all features in their screenshot editor, and an API for dynamically generating images with multiple templates. They also provide SDKs for Node.js, Ruby, Python, and PHP. Refunds for subscriptions and cancellation options are available, but there is no life-time subscription deal.
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The 20 Generative AI Coding Tools Every Programmer Should Know About
Generative AI coding tools are democratizing programming by enabling non-programmers to create software. Professional programmers can use these tools to fix bugs and improve code efficiency. Some popular generative AI coding tools include Co-Pilot, Amazon Q Developer, IBM watsonx Code Assistant, and CodeWP.
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How We Saved 10s of Thousands of Dollars Deploying Low Cost Open Source AI Technologies At Scale with Kubernetes
Learn how to deploy low-cost open source AI technologies at scale with Kubernetes for generative AI applications, using alternatives to OpenAI and running vLLM locally and on Kubernetes.
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Developing Multi-Modal Bots with Django, GPT-4, Whisper, and DALL-E
Learn how to develop a multi-modal bot using Django, GPT-4, Whisper, and DALL-E. The tutorial covers integrating artificial intelligence into web applications, creating a multi-modal bot that understands and responds to user inputs in various forms (text, voice, and images), and leveraging models like Whisper for speech transcription, GPT-4 for text generation, and DALL-E for image generation.
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Data Science Central·2y
GenAI, RAG, LLM… Oh My!
The post discusses the importance of prompt engineering and its levels of mastery in integrating Generative AI (GenAI) tools with the 'Thinking Like a Data Scientist' (TLADS) methodology. It also emphasizes the role of continuous learning and model updating in ensuring the relevancy and accuracy of LLM models. Furthermore, it highlights the users' responsibilities in actively participating in the learning cycle and introduces Reinforcement Learning through Human Feedback (RLHF) as a technique to improve LLM performance. It concludes by mentioning TLADS Step 8, which focuses on creating a learning-based User Experience (UEX) through integrative feedback systems and user-centric design.
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