Welcome to AI Today TechTalk – where we geek out about the coolest, craziest, and most mind-blowing stuff happening in the world of Artificial Intelligence! 🚀This is your AI crash course, snackable podcast-style. Think of it as your weekly dose of cutting-edge research, jaw-dropping breakthroughs, and “Wait, AI can do THAT?!” moments. We take the techy, brain-bending papers and news, break them down, and serve them up with a side of humor and a whole lot of fun.Whether you’re an AI superfan, a tech wizard, or just someone who loves knowing what’s next in the tech world, this channel has s
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Contact path
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Guest openness
Selective
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Signup to Generate a PitchWelcome to AI Today TechTalk, where we geek out about the coolest, craziest, and most mind-blowing stuff happening in the world of Artificial Intelligence! 🚀This is your AI crash course, snackable podcast-style. Think of it as your weekly dose of cutting-edge research, jaw-dropping breakthroughs, and “Wait, AI can do THAT?!” moments.
AI Today is hosted by AI Today Tech Talk. The show has published 30 episodes to date.
Recent episodes include "SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model | #ai #2025 #genai #google" (7 February 2025, 16 minutes), "Deepseek Janus-Pro: Unified Multimodal Understanding and Generation | #ai #2025 #genai #deepseek" (30 January 2025, 17 minutes), and "Memory Layers at Scale | #ai #2024 #genai #meta" (11 January 2025, 15 minutes).
AI Today publishes roughly weekly, with episodes averaging 19 minutes across 30 episodes.
Booking probability for AI Today is 19%, and the host is rated Selective on guests. AI Today requires a Pod Score of 80 or higher. AI Today's contact route on record: public web form.
The strongest fits for AI Today are IT Services & Software Development. AI Today has a technology audience.
AI Today Tech Talk hosts AI Today, a technology podcast with 30 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.
Episode #2
<p>Paper: https://arxiv.org/pdf/2501.17161 This research paper compares supervised fine-tuning (SFT) and reinforcement learning (RL) for post-training foundation models. Using novel and existing tasks involving...
Episode #1
<p>Paper: https://github.com/deepseek-ai/Janus/blob/main/janus_pro_tech_report.pdf Github: https://github.com/deepseek-ai/Janus/tree/main?tab=readme-ov-file The paper introduces Janus-Pro, an improved multimodal model...
<p>Paper: https://arxiv.org/pdf/2412.09764 This research paper explores the effectiveness of memory layers in significantly enhancing large language models (LLMs). By incorporating a trainable key-value lookup...
Episode #27
<p>Paper: https://scontent-dfw5-1.xx.fbcdn.net/... This research paper introduces Large Concept Models (LCMs), a novel approach to language modeling that operates on sentence embeddings instead of individual tokens...
Episode #26
<p>Technical Report: https://arxiv.org/pdf/2412.19437 Github: https://github.com/deepseek-ai/DeepSe... This research paper introduces DeepSeek-V3, a 671-billion parameter Mixture-of-Experts (MoE) large language model...
<p>Paper: https://arxiv.org/pdf/2309.16588 This research paper examines artifacts in vision transformer feature maps, specifically high-norm tokens appearing in non-informative image areas. The authors propose adding...
<p>Paper: https://arxiv.org/pdf/2412.09871v1.pdf The paper introduces the Byte Latent Transformer (BLT), a novel large language model architecture that processes raw byte data without tokenization. BLT dynamically...
Episode #23
<p>This research paper introduces CosyVoice 2, an improved streaming speech synthesis model. Building upon its predecessor, CosyVoice 2 utilizes advancements in large language models (LLMs) and incorporates...
<p>Blog: https://openai.com/12-days/ OpenAI announced two new large language models, o3 and o3-mini, showcasing significantly improved performance on various benchmarks, including coding, mathematics, and reasoning...
<p>Paper: https://arxiv.org/pdf/2412.14093 This research paper explores "alignment faking" in large language models (LLMs). The authors designed experiments to provoke LLMs into concealing their true preferences (e.g...
Episode #20
<p>Blog: https://blog.google/technology/google... Google announced updates to its AI video and image generation models, Veo 2 and Imagen 3, boasting state-of-the-art capabilities in realism and style diversity. These...
Episode #19
<p>Paper: https://arxiv.org/pdf/2411.01747 This research report introduces Allegro, a novel, open-source text-to-video generation model that surpasses existing open-source and many commercial models in quality and...
<p>Paper: https://arxiv.org/pdf/2411.01747 The paper "DynaSaur: Large Language Agents Beyond Predefined Actions" introduces a novel large language model (LLM) agent framework that dynamically generates and executes...
<p>Paper: https://arxiv.org/pdf/2411.17116 The paper introduces Star Attention, a novel two-phase attention mechanism for efficient Large Language Model (LLM) inference on long sequences. It improves computational...
Episode #16
<p>Paper: https://arxiv.org/pdf/2410.18967 The paper introduces Ferret-UI 2, a multimodal large language model (MLLM) that significantly improves upon its predecessor, Ferret-UI, by enabling universal user interface...
Episode #15
<p>Paper: https://arxiv.org/abs/2411.00412 This research introduces a novel two-stage training method to improve Large Language Models' (LLMs) ability to solve complex scientific problems. The method, called Adapting...
<p>Paper: https://arxiv.org/pdf/2411.02830 This research introduces Mixtures of In-Context Learners (MOICL), a novel approach to improve in-context learning (ICL) in large language models (LLMs). MOICL addresses ICL's...
Episode #13
<p>Paper: https://arxiv.org/pdf/2411.04997 Github: https://github.com/microsoft/LLM2CLIP The paper introduces LLM2CLIP, a method to improve the visual representation learning capabilities of CLIP by integrating large...
Episode #12
<p>Paper: https://arxiv.org/pdf/2411.14199 Github: https://github.com/AkariAsai/OpenScholar The research introduces OpenScholar, a retrieval-augmented large language model (LLM) designed for synthesizing scientific...
Episode #11
<p>Paper: https://arxiv.org/pdf/2401.03407 Github: https://github.com/ZhengPeng7/BiRefNet This research introduces BiRefNet, a novel deep learning framework for high-resolution dichotomous image segmentation. BiRefNet...
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