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Slides2:22EN
Matthew Berman· May 29, 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.Fine-tuningEvalsLocal inference+2
3 slides11:56EN
Matthew Berman· Nov 3, 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.Models & trainingEnterprise AIFine-tuning+2
5 slides12:03EN
Matthew Berman· Sep 6, 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.AI HistoryFoundation ModelsEvals+2
Slides0:44EN
Matthew Berman· Aug 29, 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.Fine-tuningInferenceInfrastructure & deployment
2 slides6:28EN
Matthew Berman· Aug 29, 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.Fine-tuningSynthetic dataModels & training
2 slides8:49EN
Matthew Berman· Jul 19, 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.Open source & communityFoundation ModelsAI Alignment+1
5 slides59:36EN
Matthew Berman· Jun 27, 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.Fine-tuningRetrieval-augmented generationOpen-weight models+2
5 slides19:38EN
Matthew Berman· Jun 9, 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.DistillationFine-tuningSynthetic data+2
4 slides11:42EN
Matthew Berman· May 31, 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.Fine-tuningQuantizationOpen-weight models+1
1:13:52EN
Matthew Berman· Apr 15, 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.Local inferenceOpen-weight modelsData quality & curation+2
3 slides6:50EN
Matthew Berman· Mar 19, 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.Local inferenceModels & trainingFine-tuning+1
4 slides8:19EN
Matthew Berman· Feb 15, 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.Generative mediaPrompting & in-context learningProduct & UX+1