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Thomas Poetter

San Jose, United States

More than 20 years of AI experience (Artificial Intelligence / Computer Vision):
Key Skills: Deep Learning (CNN, RNN, TensorFlow, PyTorch, etc.), Natural Language Processing: LLMs, LMMs, RAG, LoRA, LlamaIndex, RAGChain, Transformers, CodeTF, Parameter-Efficient Fine-Tuning Methods (PEFT) for Pretrained Language Models (PLMs), DPO, PPO, Graph Neural Networks (GNNs), Knowledge Graphs (KGs), LLMOps, LMMOps, RLHF, RLAIF, SSMs, H3, Mixture of Experts (MoE), MetaGPT, Reinforcement Learning (RL), Q* Search/Q-Learning), Policy NN, Value NN, MCTS, OpenAI CLIP Architecture, DocLLM.
Data Science (Apache Spark MLlib, Mahout, R, spaCy, Anaconda), Hybrid Models (predefined structures + neural networks + weights/stochastics, e.g.), Hybrid Models (predefined structures + neural networks + weights/stochastics) e.g. LSTM (Long Short-Term Memory), GRU (Gated Recurrent Units), Attention, Feast AI), ONNX, PMML, OpenScoring.io, storage of deep learning intermediate results + models, knowledge representation and inference (reasoning, drawing conclusions), semantics, virtualisation, management with Docker, Kubernetes, Airflow, etc.

Special Strength in AI: Many companies/teams cannot directly use modern AI, because they lack the many terabytes of training data for it. Because AI was my main field of study (at the DFKI in Kaiserslautern, until the AI hype from about 2015 the only German AI research center), I know dozens of classical low resource/low data AI methods and furthermore, I have been involved in probabilistic programming with Stan (mc-stan.org), Edward, Infer.Net, Pyro, Julia/MLJ.jl + MIT Gen.jl, Probabilistic Soft Logic (PSL), ProbLog, Factorie as well as PyTorch/ProbTorch (differentiable programming), in order to be able to use all these technologies as AI-enabling- or customer project enabling technologies.

Available For: Advising, Authoring, Consulting, Speaking
Travels From: San Jose

Thomas Poetter Points
Academic 0
Author 8
Influencer 80
Speaker 0
Entrepreneur 0
Total 88

Points based upon Thinkers360 patent-pending algorithm.

Thought Leader Profile

Portfolio Mix

Company Information

Company Type:
Minimum Project Size: Undisclosed
Average Hourly Rate: Undisclosed
Number of Employees: Undisclosed
Company Founded Date: Undisclosed
Media Experience: 20 Years
Last Media Training: 06/03/2024
Last Media Interview: 06/03/2024

Areas of Expertise

5G
Agentic AI 30.13
Agile 30.07
AI 30.05
AI Governance 30.41
Analytics
AR/VR
Autonomous Vehicles
Big Data
Blockchain
Business Continuity
Business Strategy
Change Management
Climate Change
Cloud
Coaching
Creativity
CRM
Cryptocurrency 30.13
CSR
Customer Experience
Cybersecurity 30.05
Data Center
DevOps
Digital Disruption
Digital Twins
EdTech
Entrepreneurship
ERP
FinTech
Future of Work
GovTech
Health and Safety
HealthTech
Innovation 30.03
InsurTech
IoT
IT Leadership 30.19
IT Operations
IT Strategy 30.45
Leadership
Lean Startup
Marketing
Metaverse
NFT
Open Innovation
Open Source
Predictive Analytics
Privacy
Product Management
Project Management
Renewable Energy
Risk Management 30.11
RPA
Security
Smart Cities
Startups
Supply Chain
Sustainability

Industry Experience

Aerospace & Defense
Automotive
Chemicals
Consumer Products
Engineering & Construction
Federal & Public Sector
Financial Services & Banking
Healthcare
High Tech & Electronics
Higher Education & Research
Insurance
Manufacturing
Media
Oil & Gas
Pharmaceuticals
Professional Services
Retail
Telecommunications
Travel & Transportation
Utilities
Wholesale Distribution

Publications & Experience

8 Article/Blogs
Q-Day in the Boardroom: A 2026 Playbook for Willow-Class Hardware & Quantum-Safe Crypto
Thomas Poetter
December 29, 2025
Someone may already be storing your ciphertext in a future‑decryption pipeline. A technical convergence — photonic quantum advantage, hour‑scale qubit coherence, AI‑driven algorithm discovery, and accelerating Willow‑class and scale‑out hardware roadmaps — compresses the timeline for large‑scale cryptanalysis. For IT managers the imperative is urgent and concrete: build awareness, secure funding, and run a 12‑month, business‑driven program in 2026 to move toward practical cryptography‑quantum‑safe (PCQ). Prioritize decipherable archival risk (harvest‑now, decrypt‑later), demand vendor accountability, prove nondisruptive migration patterns with pilots and hardware proofs, and harden crown‑jewel assets.

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Tags: Cybersecurity, IT Strategy, Risk Management

From Classical Secure to Quantum Safe: A Practical Roadmap for IT Leaders
Thomas Poetter
December 18, 2025
Prepare for the quantum era! A roadmap for IT leaders on becoming quantum-safe. Mitigate risks with post-quantum cryptography and boost cybersecurity. Photonic quantum advantage, qubit stability, AI-driven quantum algorithm discovery, and hardware scale-up compress the credible threat horizon. For IT managers, post-quantum transition is an immediate, fundable program (2025–2028), not a distant research topic.

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Tags: Cryptocurrency, Cybersecurity, Innovation

Anticipatory Governance and Agentic Foresight: Designing Decisions That Withstand Rapid AI Change
Thomas Poetter
December 11, 2025
The next technological shock won’t arrive with a press release from a CEO on a stage in San Francisco. Instead, it will whisper through faint, easily dismissed signals in the developer ecosystem—a sudden spike in repository forks on GitHub, a new method of model quantization on arXiv, or a silent shift in API consumption patterns. Teams that rely on static forecasting and traditional risk matrices will be blindsided by these shifts; teams that master Anticipatory Governance will turn this uncertainty into a defensible competitive moat (OECD, 2025a).
We have officially transitioned from the era of Generative AI—defined by probabilistic content creation and chatbots—to the era of Agentic AI: systems capable of reasoning, planning, and executing multi-step workflows autonomously. This shift, confirmed by the 2025 AI Index Report (Stanford HAI, 2025), represents a structural discontinuity in the business environment. The linear extrapolation of past trends is no longer a valid predictor of future capability (Acemoglu, 2024).
This article outlines a "Future-Safe" Operating Model. It argues that the primary objective of modern leadership is no longer optimization, but the preservation of optionality. It details a rigorous framework to detect weak signals using 2025 data, stress-test strategies against thousands of probabilistic futures using reasoning models, and deploy decision architectures that survive technological volatility.

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Tags: AI, AI Governance, IT Leadership

Automation and the Future of Work: Risks, Transformation, and Human Value in 2026
Thomas Poetter
December 09, 2025
"Machines can do the predictable; humans must master the unpredictable."
Automation will redefine jobs and power; the decisive question is not whether machines can replace us, but how we reorganize value, skills, and institutions so that humans remain indispensable.

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Tags: Agentic AI, IT Leadership, Risk Management

Vertical and Horizontal AI: Strategic Applications, Risks, and Managerial Implications
Thomas Poetter
December 07, 2025
Explore vertical and horizontal AI agents' strategic applications, risks, and managerial impact. Unlock the power of vertical AI solutions!

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Tags: Agentic AI, IT Strategy, Risk Management

Partial Automation: A Human-Centric Approach to Artificial Intelligence and a foresight for the future
Thomas Poetter
December 01, 2025
Explore partial automation: a human-centric AI approach. Discover how it's shaping the future with strategic foresight and responsible artificial intelligence.

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Tags: Agentic AI, AI, AI Governance

False Statistics around Inflation
LinkedIn
May 02, 2024
If we define the “real inflation” is the development of the prices of a typical shopping basket of popular affordable products for the worker class without any further tricks or manipulations but instead taking into account the lowering of quality and shrinkflation, then there were ~10% inflation in those years which officially showed ~2% inflation.

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Tags: Agile, AI

How the Ahr Valley Flood Failure demonstrated the Deficits that our Global Addressing of Problems also exhibits
LinkedIn
July 15, 2022
We globally fail to see and react towards the 15+ wicked problems and the mechanisms behind that are mostly the same as around the Ahr valley flood. What unfolded quickly in the case of the flood is unfolding more slowly on a global level regarding these 15+ wicked problems of which global warming with floods/droughts/earthquakes and other disasters is only one category. The mechanisms to diagnose and resolve the issues are also not in place on a global level, not even in the richer Western World.

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Tags: Agile, AI, HR

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