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Coffee With Developers • May 9, 2025

Google Gemini: Open Source and Deep Thinking Models - Sam Witteveen

Sam Witteveen

Sam Witteveen reveals how Google’s open-weights Gemma brings massive multimodal AI to your local machine. Discover why deep reasoning architectures are elevating engineers into high-level system architects.

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#1 about 2 min

Distinguishing artificial intelligence from deep learning

The broad marketing term of artificial intelligence often masks foundational deep learning capabilities.

#2 about 2 min

Impact of artificial intelligence hype on research sharing

A surge in industry resources has increased secrecy among major machine learning research labs.

#3 about 4 min

Licensing and capabilities of open weights models

Open weights models offer developers commercial flexibility without releasing underlying proprietary training datasets.

#4 about 3 min

The fundamental training phases of language models

Language models convert raw text tokens into coherent outputs through complex pre-training and reinforcement cycles.

#5 about 3 min

Comparing on-premise execution with proprietary cloud offerings

Hosting smaller models on-premise provides critical data privacy alternatives to proprietary cloud architectures.

#6 about 4 min

Achieving high inference performance in smaller model sizes

Distillation techniques compress massive capabilities into lightweight frameworks suited for direct consumer hardware execution.

#7 about 2 min

Expanding accessibility with extensive multilingual training data

Training architectures across diverse linguistic datasets improves foundational accessibility beyond western languages.

#8 about 5 min

Processing unstructured information using multimodal capabilities

Multimodal systems instantly extract logic by connecting cross-references across text, audio, and visual inputs.

#9 about 5 min

Advancements in generative typography and video creation

Modern visual architectures correctly render text overlays and synthesize complex motion across dynamic scenes.

#10 about 4 min

Automating audio manipulation and dynamic video editing

Coupling timestamp alignments with synthetic voice generation enables direct structural edits to existing media.

#11 about 4 min

Implementing prompt patterns for adaptive technical education

Directly prompting generative models constructs adaptive technical tutorials for non-traditional skill acquisitions.

#12 about 6 min

Evaluating logic via internal chain of thought processing

Deep reasoning models process intermediate logic internally before delivering final conclusions to complex prompts.

#13 about 7 min

Accelerating code generation through autonomous agent workflows

Autonomous coding agents recursively run testing validations to iteratively refine their generated function patches.

#14 about 4 min

Rethinking developer environments with conversational code assistance

Deeply integrated workspace extensions map complex architectural requests far better than standard text interfaces.

#15 about 3 min

Provisioning local runtimes for open weights models

Developers rapidly scale offline experimentation by bridging downloadable model configurations with desktop orchestration engines.

Matching moments

4:04 min

Building practical AI agents using Google Gemini

Philipp Schmid Philipp Schmid · World Congress 2025

3:02 min

Understanding Google Gemini history and available context models

5:05 min

Exploring popular generative AI models and applications

Mary Grygleski Mary Grygleski · LIVE

3:13 min

Embedding generative AI in enterprise software platforms

Mike Butcher Mike Butcher +3 · World Congress 2024

2:44 min

Understanding the differences between Gemma and Gemini models

3:23 min

The rapid evolution of generative artificial intelligence capabilities

Jens Echterling Jens Echterling · World Congress 2025

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Open session

World Congress 2026 North America

September 23, 2026 · 10:00–17:00

Stage 11

Building Stuff with GenAI - The Open Minded Workshop beyond OpenAI

Andreas Erben

CTO for Applied AI and Metaverse at daenet

Andreas Erben
Open session

World Congress 2026 North America

September 24, 2026 · 17:30–18:00

Stage 6

No Single Model to Rule Them All: Building Resilient AI Agents Across Open & Closed LLMs

Emmanuel Acheampong

Senior Manager Developer Relations at Crusoe AI

Emmanuel Acheampong
Open session

World Congress 2026 North America

September 25, 2026 · 10:20–10:50

Tech Leaders Stage

Democratizing AI: Why Open Models Are Essential for the Next Era

Mitesh Patel, Joey Conway, Olivier Lacombe, Varun Vontimitta

Mitesh Patel
Joey Conway
Olivier Lacombe
Varun Vontimitta
Open session

World Congress 2026 North America

September 24, 2026 · 14:10–14:40

Stage 5

Edge AI: Running Agentic Intelligence Where Internet Can't Reach

Nitin Eusebius

AWS - Principal Solutions Architect

Nitin Eusebius
Open session

World Congress 2026 North America

September 23, 2026 · 10:45–12:45

Stage 9

Local AI Workshop for Beginners: Private ChatGPT Experience on Your Own Computer

Jason Stine

Fullstack Software Engineer at Centivo

Jason Stine
Open session

World Congress 2026 North America

September 25, 2026 · 16:50–17:20

Stage 7

You Can’t Re-Run Sunlight: Designing ML Data Architectures for Physical AI

An Phan

Senior Data Infrastructure Engineer @ Hippo Harvest

An Phan

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