An essential guide to understanding Anthropic Claude, from safe AI foundations to advanced workflows, agents, and practical applications.
Artificial intelligence has rapidly evolved from experimental research into a practical tool that powers applications across industries. Among the new generation of AI systems, Anthropic's Claude stands out as...
GPT-2 was introduced in 2019 but we can learn how the fundamentals of transformer training and inference work by rebuilding GPT-2 in PyTorch.
GPT-2 was introduced in 2019 and primarily built within the TensorFlow framework. Let's take a look at how we can reproduce GPT-2 with PyTorch while following the methodology outlined in the accompanying GPT-2 research paper.
Prompt engineering language models lacks necessary refinement especially for enterprise solutions. Optimize your language models with DSPy!
Optimizing language models is an important task as organizations integrate generative AI capabilities into their business processes. Relying on manual prompt engineering introduces risk, biases, and other problems. Continue reading to learn how to mitigate these risks with DSPy.
LLaVA, among other multimodal AI models, leaps from standalone large language models and allows us to engage with AI in novel ways.
Understanding our world often requires interpreting stimuli from multiple sources including through vision or text. LLaVA accomplishes this by combining a vision encoder with a large language model. Continue reading to learn how to leverage multimodal AI with Databricks and LLaVA! 🌋
I build data and AI solutions to deliver impact and value for organizations large and small.
I earned my Master's (M.S.) from Carnegie Mellon University and my Bachelor's (B.S.) from the Pennsylvania State University. All views on my website are my own and do not represent the organizations I work with unless clearly stated.
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