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1:12ENA Sponsored Look at Higgsfield's Image and Video APIMatthew Berman · Forward FutureMatthew Berman uses a real-versus-AI video comparison to introduce Higgsfield's model catalog and generation-based API billing.
0:55ENGenerating Short AI Videos with Claude and HiggsfieldMatthew Berman · Forward FutureMatthew Berman demonstrates a prompt for whimsical videos and describes connecting Higgsfield to Claude.
1:57:29ENFrontier vision models score 12.5%: Joseph Nelson on the real waterline of computer visionPresenta: Nathan LabenzThe Roboflow CEO tells Nathan Labenz why vision still lags language, how to distill SAM 3 into an edge model for Wimbledon, and why the United States has almost never led open-source vision.
11:31ENExploring Google’s Project Genie: Interactive Worlds with Genie 3AlexAlex tests generated racetracks, alien structures and cloud landscapes, showing both the prototype’s creative options and its control limitations.
1:20ENLTX-2 Brings Open-Weight Audio and Video Generation to Local WorkflowsMatthew Berman · Forward FutureMatthew Berman discusses NVIDIA’s ComfyUI demonstration, creative controls and the prospects for locally generated video.
2:12ENNVIDIA’s Alpamayo and the Promise of Synthetic Data for Autonomous DrivingMatthew Berman · Forward FutureMatthew Berman discusses the CES 2026 announcement and why simulated driving scenarios could help developers train autonomous-vehicle systems.
1:58ENGPT-5.2 at Launch: Benchmark Results, Demos and API PricingMatthew Berman · Forward FutureMatthew Berman reviews OpenAI’s December 2025 announcement, highlighting selected evaluations, product demos and the cost increase over GPT-5.1.
28:27ENSora 2 in Practice: Cameos, Camera Direction and Video Generation ErrorsMatthew Berman · Forward FutureMatthew Berman surveys early Sora 2 clips, testing likenesses, hands, motion, graphics and physics while pointing out where the generated scenes break down.
9:45ENMatthew Berman Reviews the First Reactions to Gemini's Nano Banana Image ModelMatthew Berman · Forward FutureEarly creators combine Google's image editor with 3D and video tools, while exposing errors, limitations, and safety questions in the results.
27:40ENSeedance 1.0 vs. Veo 3: An Informal Text-to-Video ComparisonMatthew Berman · Forward FutureMatthew Berman compares visual quality, motion and prompt adherence across gymnastics, action, animation and fantasy scenes.
9:10ENGuiding AI Image Generation with Blender and ComfyUIMatthew Berman · Forward FutureMatthew Berman walks through NVIDIA’s RTX blueprint for turning a simple Blender scene and a text prompt into a generated image, from installation to editing the result.
16:02ENRunway Gen-4 Examples: Cinematic Motion, Style and Visible ErrorsMatthew Berman · Forward FutureMatthew Berman reviews early generated clips, praising their visual detail while identifying awkward interactions and inconsistent physics.
17:03ENMatthew Berman Explores GPT-4o Image Generation and Its LimitsMatthew Berman · Forward FutureFrom animated trailer remakes to infographics and interface mockups, early examples show creative possibilities alongside persistent errors.
6:44ENTesting DeepSeek Janus-Pro for Image Understanding and GenerationMatthew Berman · Forward FutureMatthew Berman tries the 7B multimodal model on diagrams, memes and image prompts using a sponsored cloud GPU demonstration.
3:53:49ENWith One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4oPresenta: Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.
13:31ENGoogle Veo 2: Cinematic Controls, Realistic Scenes and Motion LimitsMatthew Berman · Forward FutureMatthew Berman reviews Google’s 2024 video-generation examples, compares selected outputs with Sora and points out where movement or prompt adherence breaks down.
14:23ENSora’s Initial Release: Storyboards, Remix and a Launch-Day TestMatthew Berman · Forward FutureMatthew Berman explores the 2024 video generator’s editing tools and reports mixed results from his first attempts.
54:45ENA Few Megabytes of Doom and a Few Gigabytes of Model: Why Runway Bets on GeneralizationPresenta: Nathan LabenzCTO Anastasis Germanidis tells The Cognitive Revolution why video is a fuller record of the world than text, why physics shows up without being programmed in, and how a small lab competes with unlimited compute.
11:14ENPixtral 12B: Testing a 2024 Vision-Language ModelMatthew Berman · Forward FutureMatthew Berman runs informal image, text and interface-generation tests of Mistral’s Pixtral on a sponsor-provided cloud GPU.
11:23ENGameNGen: Simulating DOOM with a Diffusion ModelMatthew Berman · Forward FutureMatthew Berman examines a 2024 research demonstration that generates an interactive DOOM-like game frame by frame, and considers what such systems might eventually enable.
0:48ENTesting Grok 2's Image Generation With Public-Figure PromptsMatthew Berman · Forward FutureMatthew Berman reviews fictional images and tries two prompts in a brief 2024 demonstration.
12:17ENTesting Gemini 1.5 Pro on Code, Reasoning, Images and VideoMatthew Berman · Forward FutureMatthew Berman compares standard and experimental Gemini versions in an informal 2024 review, finding mixed results and repeated output errors.
46:47ENEditing Video Like a Document: How Descript Puts AI in the Copilot SeatPresenta: Nathan LabenzDescript CEO Andrew Mason on Underlord, why the timeline had to die, and what a ten-times-more-expensive editor would look like.
1:03:22ENA 40-person team at $35 million ARR: HeyGen made AI avatars a business, not a demoPresenta: Nathan LabenzJoshua Xu and Benchmark’s Victor Lazarte tell Nathan Labenz how a camera-replacement product grew past 40,000 business customers — and why half the faces on this episode are fake.
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