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2:22EN
Matthew Berman· 29. Mai 2026Pioneer Agent and Automated Fine-Tuning of Small ModelsMatthew Berman · Forward FutureIn a Fastino-sponsored video, Matthew Berman describes a system that automates parts of model adaptation and discusses its reported benchmark results.
11:56ENMatthew Berman· 3. Nov. 2024IBM Granite 3.0 and InstructLab: Small Models for Enterprise AIMatthew Berman · Forward FutureMatthew Berman reviews IBM's 2024 model family and its approach to adding domain knowledge. IBM partnered on the video and invited him to its event.
12:03ENMatthew Berman· 6. Sept. 2024Reflection 70B: Self-Correction Claims and the Limits of a 2024 DemoMatthew Berman · Forward FutureMatthew Berman reviews a model trained to generate reflection steps. Its initial benchmark claims later proved difficult for independent evaluators to reproduce.
0:44ENMatthew Berman· 29. Aug. 2024NVIDIA Adds Multi-LoRA Serving to Its RTX AI ToolkitMatthew Berman · Forward FutureIn an NVIDIA-partnered video, Matthew Berman describes using multiple adapters with one base model and a vendor-reported throughput gain.
14:30ENMatthew Berman· 3. Juli 2024Retrieval-Augmented Generation: External Knowledge, Embeddings and SearchMatthew Berman · Forward FutureMatthew Berman introduces RAG using customer-service, company-document and automotive-manual examples, then explains vector retrieval and agents.
6:28ENMatthew Berman· 29. Aug. 2023A Historical GPT-3.5 Fine-Tuning WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates generating synthetic examples in Colab and training a model to use a distinctive tone.
13:19ENMatthew Berman· 17. Aug. 2023Testing WizardLM 70B: Setup, Coding and Reasoning ResultsMatthew Berman · Forward FutureMatthew Berman runs a quantized Llama 2-based model through an informal collection of coding, writing, arithmetic and logic prompts.
8:49ENMatthew Berman· 19. Juli 2023Llama 2’s 2023 Release: Model Sizes, License and SafetyMatthew Berman · Forward FutureMatthew Berman reviews Meta’s Llama 2 paper, its commercial license, model variants and safety evaluations.
59:36ENMatthew Berman· 27. Juni 2023Pascal Pfeiffer on Retrieval, Open Models, Kaggle and Fine-Tuning with H2O LLM StudioMatthew Berman, Pascal Pfeiffer · Forward FutureIn a 2023 interview, H2O.ai’s Pascal Pfeiffer explains document retrieval and parameter-efficient fine-tuning, reflects on Kaggle competitions and demonstrates LLM Studio. He and Matthew Berman also consider coding assistants and unverified rumors about model architecture.
19:38ENMatthew Berman· 9. Juni 2023Orca: Teaching a Smaller Model with GPT-4 ExplanationsMatthew Berman · Forward FutureMatthew Berman reviews Microsoft Research’s 2023 Orca paper and its approach to training a 13-billion-parameter model on detailed teacher responses.
11:42ENMatthew Berman· 31. Mai 2023Guanaco and QLoRA: A 2023 Fine-Tuning and Model TestMatthew Berman · Forward FutureMatthew Berman reviews the QLoRA paper, explains the reported memory savings and tries Guanaco 65B on an informal prompt set.
1:13:52ENMatthew Berman· 15. Apr. 2023Andriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.
6:50ENMatthew Berman· 19. März 2023Running LLaMA and Alpaca Locally: A 2023 Dalai TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup on a MacBook Air and explains the settings that control generation.
8:19ENMatthew Berman· 15. Feb. 2023Leonardo.Ai in 2023: Generating Images, Remixing Models and Editing a CanvasMatthew Berman · Forward FutureMatthew Berman walks through Leonardo.Ai’s early image-generation interface, from style models and settings to community remixes, custom training and the beta canvas. Features and pricing have changed since this February 2023 demonstration.