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Model: "dall-e-3"
Kolmogorov-Arnold Networks: MLP killers or just spicy MLPs?
gpt-5 gpt-4 dall-e-3 openai microsoft learnable-activations mlp function-approximation interpretability inductive-bias-injection b-splines model-rearrangement parameter-efficiency ai-generated-image-detection metadata-standards large-model-training max-tegmark ziming-liu bindureddy nptacek zacharynado rohanpaul_ai svpino
Ziming Liu, a grad student of Max Tegmark, published a paper on Kolmogorov-Arnold Networks (KANs), claiming they outperform MLPs in interpretability, inductive bias injection, function approximation accuracy, and scaling, despite being 10x slower to train but 100x more parameter efficient. KANs use learnable activation functions modeled by B-splines on edges rather than fixed activations on nodes. However, it was later shown that KANs can be mathematically rearranged back into MLPs with similar parameter counts, sparking debate on their interpretability and novelty. Meanwhile, on AI Twitter, there is speculation about a potential GPT-5 release with mixed impressions, OpenAI's adoption of the C2PA metadata standard for detecting AI-generated images with high accuracy for DALL-E 3, and Microsoft training a large 500B parameter model called MAI-1, potentially previewed at Build conference, signaling increased competition with OpenAI. "OpenAI's safety testing for GPT-4.5 couldn't finish in time for Google I/O launch" was also noted.
1/10/2024: All the best papers for AI Engineers
chatgpt gpt-4 dall-e-3 stable-diffusion deepseek-moe openai deepseek-ai prompt-engineering model-release rate-limiting ethics image-generation moe collaborative-workspaces data-privacy abdubs darthgustav
OpenAI launched the GPT Store featuring over 3 million custom versions of ChatGPT accessible to Plus, Team, and Enterprise users, with weekly highlights of impactful GPTs like AllTrails. The new ChatGPT Team plan offers advanced models including GPT-4 and DALL·E 3, alongside collaborative tools and enhanced data privacy. Discussions around AI-generated imagery favored DALL·E and Stable Diffusion, while users faced rate limit challenges and debated the GPT Store's SEO and categorization. Ethical considerations in prompt engineering were raised with a three-layer framework called 'The Sieve'. Additionally, DeepSeek-MoE was noted for its range of Mixture of Experts (MoE) model sizes. "The Sieve," a three-layer ethical framework for AI, was highlighted in prompt engineering discussions.
1/1/2024: How to start with Open Source AI
gpt-4-turbo dall-e-3 chatgpt openai microsoft perplexity-ai prompt-engineering ai-reasoning custom-gpt performance python knowledge-integration swyx
OpenAI Discord discussions revealed mixed sentiments about Bing's AI versus ChatGPT and Perplexity AI, and debated Microsoft Copilot's integration with Office 365. Users discussed DALL-E 3 access within ChatGPT Plus, ChatGPT's performance issues, and ways to train a GPT model using book content via OpenAI API or custom GPTs. Anticipation for GPT-4 turbo in Microsoft Copilot was noted alongside conversations on AI reasoning, prompt engineering, and overcoming Custom GPT glitches. Advice for AI beginners included starting with Python and using YAML or Markdown for knowledge integration. The future of AI with multiple specialized GPTs and Microsoft Copilot's role was also explored.
12/20/2023: Project Obsidian - Multimodal Mistral 7B from Nous
gpt-4 gpt-3.5 dall-e-3 nous-research teknim openai multimodality image-detection security-api bias facial-recognition healthcare-ai gpu-optimization prompt-engineering vision
Project Obsidian is a multimodal model being trained publicly, tracked by Teknium on the Nous Discord. Discussions include 4M: Massively Multimodal Masked Modeling and Reason.dev, a TypeScript framework for LLM applications. The OpenAI Discord community discussed hardware specs for running TensorFlow JS for image detection, security API ideas for filtering inappropriate images, and concerns about racial and cultural bias in AI, especially in facial recognition and healthcare. Challenges with GPT-3.5 and GPT-4 in word puzzle games were noted, along with GPU recommendations prioritizing VRAM for AI inference. Users also debated GPT-4's vision capabilities, limitations of DALL·E 3, platform access issues, and prompting strategies for better outputs.