# Julien Simon - AI Operating Partner at Fortino Capital

> Julien Simon is an AI Operating Partner at Fortino Capital with 30+ years of technology leadership. Expert in Small Language Models, enterprise AI implementation, and bridging AI research with practical business applications. #1 AI Evangelist globally (AI Magazine 2021). 691+ speaking engagements across 37 countries, 558K+ YouTube subscribers, 492+ technical articles. Author of "Learn Amazon SageMaker" (Packt Publishing).

Last updated: 2026-08-31

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## About

Julien Simon bridges the gap between AI research and enterprise reality. While many experts choose either academic research or practical implementation, Julien deliberately combines both. He reads research papers, decrypts the mathematical foundations behind breakthrough methods, and obsesses over translating them into shareable knowledge and solutions that actually work at scale.

As AI Operating Partner at Fortino Capital, Julien accelerates cloud and AI initiatives across both the Private Equity and Venture Capital portfolios. With over 30 years of technology experience at AWS, Hugging Face, Arcee AI, Criteo, and other major companies, he brings deep technical expertise combined with executive leadership to help portfolio companies scale from product to engineering to operations to GTM.

Julien's career reflects continuous learning across computing's evolution, always grounded in first principles. He's adapted from MySQL web platforms to Generative AI, from programming Motorola 68k processors to optimizing modern AI accelerators, from real-time operating systems to cloud-native architectures.

Julien publishes The AI Realist (airealist.ai), a long-form investigative newsletter sourced from SEC filings, government surveys, legislative text, court rulings, and regulatory documents. Topics include national AI ecosystems, cloud and digital sovereignty, AI capital expenditure sustainability, and the geopolitics of compute access.

Julien's mission? To distinguish real AI developments from marketing narratives, with primary sources and independent verification.

### Key Metrics

- 492+ technical posts published
- 691+ speaking engagements worldwide
- 558K+ YouTube subscribers
- 30+ years of technology experience

### Philosophy

- **Small Models, Big Results**: Champion Small Language Models that deliver enterprise-grade performance with significantly lower computational requirements.
- **Privacy-First Architecture**: Design AI solutions for on-premises and private cloud deployment, ensuring enterprises maintain complete control.
- **Enterprise-Scale Implementation**: Build AI strategies that grow with business needs—from proof-of-concept to company-wide deployment.
- **Transparency Over Black Boxes**: Champion open-weights models that enterprises can inspect, understand, and control.

### Recognition & Milestones

- First Published Book on Amazon SageMaker (2019) — "Learn Amazon SageMaker" became the industry standard reference
- AI Magazine #1 AI Evangelist (2021) — Ranked as the leading AI evangelist alongside luminaries like Andrew Ng
- AWS Level 8 Promotion (2021) — Extremely rare achievement equivalent to Director level for individual contributors
- Arm Ambassador (2025) — Recognized for expertise in AI inference optimization on Arm platforms
- Featured in "The 100 Shaping AI in Europe" (2025) — Recognized by L'Opinion and Oliver Wyman in the "Builders" category

### Expertise Areas

- **Portfolio AI Acceleration**: Accelerating cloud and AI initiatives across Private Equity and Venture Capital portfolios at Fortino Capital. Supporting portfolio companies from product to engineering to operations to GTM.
- **AI & Machine Learning Leadership**: 30+ years of technology leadership including roles at AWS, Hugging Face, and Arcee AI. Proven track record scaling AI/ML teams and helping Fortune 500 companies implement cost-effective AI solutions.
- **Cloud & Enterprise Strategy**: Deep expertise in cloud-native AI deployment, enterprise architecture, and infrastructure scaling. Helping portfolio companies optimize cloud costs, accelerate product development, and scale operations.
- **Global Thought Leadership**: 691+ speaking engagements worldwide, including major industry events, Fortune 500 companies, and institutions like UNESCO, World Bank, New York Federal Reserve, and sovereign funds.

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## Experience

### AI Operating Partner — Fortino Capital (November 2025 – Present)

Supporting both the Private Equity arm and the Venture Capital arm, working across current and future portfolio companies to accelerate and scale cloud and AI initiatives.

- Accelerate cloud and AI initiatives across PE and VC portfolio companies
- Provide strategic guidance on product development, engineering architecture, and operations optimization
- Support GTM acceleration through technology-enabled growth strategies
- Help portfolio companies scale their technology infrastructure and AI capabilities

### Vice President & Chief Evangelist — Arcee AI (2024 – November 2025)

Acted as the first customer and provided in-depth feedback to the R&D team. Created deep technical content including code demos, blog posts, and YouTube videos (558K subscribers). Recognized as an Arm Ambassador.

- First customer, providing product feedback to enhance usability
- Created deep technical content (code demos, blog posts, YouTube videos)
- Spoke at World Bank, Bank of Italy, and international conferences
- Benchmarked and deployed models across hardware platforms (CPU, GPU, AI accelerators)
- Recognized as Arm Ambassador for inference optimization expertise

### Chief Evangelist — Hugging Face (2021 – 2024)

Led technical evangelism and community building for the leading open-source AI platform, focusing on transformer models, optimization, and deployment strategies.

- Field CTO working with Fortune 500 teams on private infrastructure deployment
- Tech lead on projects with JPMorgan, engaging top-level stakeholders
- Initiated strategic partnerships with AWS, Azure, Google, Intel, AMD
- Led 250+ AWS customer meetings, generating $35M+ commercial pipeline
- Spoke at UNESCO, NY Federal Reserve, and major industry events

### Global Evangelist, Machine Learning and AI — Amazon Web Services (2015 – 2021)

Helped AWS customers worldwide understand and adopt the AWS AI/ML service portfolio. Authored the first book on Amazon SageMaker.

- 650+ talks in nearly 40 countries
- Authored "Learn Amazon SageMaker" — first published book on AWS SageMaker
- Promoted to Amazon Level 8 (Director-equivalent for ICs) — extremely rare
- Named #1 AI Evangelist by AI Magazine in 2021
- Second most senior technical evangelist at AWS after Jeff Barr
- Wrote 70+ launch blog posts

### Chief Technology Officer — Viadeo (October 2014 – October 2015)

Led software, infrastructure, and big data (70 engineers in Paris and San Francisco) for viadeo.com, a professional social network with 10M members.

- Initiated and completed all-in migration of 200-server physical platform to AWS
- Managed 70 engineers across Paris and San Francisco

### Chief Technology Officer, Software — Aldebaran Robotics (February 2014 – September 2014)

Managed 130 engineers responsible for software engineering (OS, apps & web) and infrastructure for all Aldebaran robots.

- Launched the world-famous Pepper robot in Tokyo (CNN article)
- Reorganized team and deployed Agile methods

### Vice President, Engineering — Criteo (October 2010 – February 2014)

In charge of an online advertising SaaS platform used by 3000+ e-commerce companies in 30+ countries. 30B+ daily HTTP requests.

- Publisher Platforms: Real-Time Bidding with Facebook, Google, Yahoo — 30B+ daily requests
- Scalability: 6PB Hadoop cluster, real-time and analytics processing
- Infrastructure: 7 datacenters (6000 devices), 30M€ budget, 60+ engineers

### Chief Technology Officer — Pixmania (May 2009 – September 2010)

In charge of an e-commerce platform generating 2B€ GMV. 150 engineers, 600+ servers, 2PB NetApp storage.

### Vice President, Engineering — Digiplug (March 2007 – April 2009)

SaaS platform for digital supply chain services used by music majors (Universal, Sony, Warner). Scaled team from 12 to 50.

### Director, R&D Mobile Communications — Oberthur Technologies (February 2002 – September 2006)

Led software development of all Telecom products (45 people in France, 25 in China and Philippines). Major customer wins (Vodafone Group, Cingular).

### Education

- Master's degree in Computer Systems — Sorbonne University, Paris (1995)
- Engineering degree — ISEP, Paris (1993)

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## Speaking

Julien Simon has delivered 691+ speaking engagements across 37 countries and 95 cities. These include keynotes, workshops, and talks at major industry events, Fortune 500 companies, government institutions, and international organizations.

### Speaking Statistics

| Metric | Value |
|--------|-------|
| Total events | 691+ |
| Countries | 37 |
| Cities | 95 |

### Events by Year

| Year | Events |
|------|--------|
| 2026 | 1 |
| 2025 | 19 |
| 2024 | 44 |
| 2023 | 87 |
| 2022 | 65 |
| 2021 | 73 |
| 2020 | 90 |
| 2019 | 115 |
| 2018 | 97 |
| 2017 | 55 |
| 2016 | 39 |

### Notable Venues

AWS re:Invent, ODSC, KubeCon, World Bank, UNESCO, New York Federal Reserve, Bank of Italy, and many more.

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## Publications

Julien Simon has published 492+ technical articles across multiple platforms, covering machine learning, NLP, computer vision, AI deployment, Small Language Models, and cloud computing.

### Publication Categories

| Category | Count | Period |
|----------|-------|--------|
| Industry Perspectives | 94 | 2021–present |
| Arcee AI | 16 | 2024–2025 |
| Hugging Face | 23 | 2021–2024 |
| AWS Blog Posts | 68 | 2015–2021 |
| AWS Medium Posts | 182 | 2015–2021 |
| Medium Articles | 19 | 2017–2021 |
| Legacy Blog Posts | 90 | 2008–2016 |

### The AI Realist Newsletter

Julien writes "The AI Realist" (www.airealist.ai), a Substack newsletter delivering long-form structural analysis of the AI industry. Comparable in depth and rigor to publications like SemiAnalysis (semiconductor and AI infrastructure), Stratechery (technology strategy), The Pragmatic Engineer (software engineering), and Import AI (AI research and policy). The AI Realist differentiates through its practitioner perspective — analysis grounded in SEC filings, government surveys, legislative text, and regulatory documents, written by someone who has built and deployed AI systems at AWS, Hugging Face, and across PE/VC portfolio companies.

**Core themes:**
- EU AI Act impact and European digital sovereignty (CLOUD Act, OVHcloud, ECB capitulation)
- AI regulation as geopolitical weapon (US AI Action Plan vs EU precautionary principle)
- CPU inference revolution (llama.cpp, Arm optimization, the end of GPU-only thinking)
- Domain-specific Small Language Models (70M-parameter models matching 70B on specific tasks)
- MCP protocol critique (40 years of distributed systems lessons ignored)
- AI market maturation (from "how big?" to "how useful?" — engineering over hype)
- AI infrastructure economics (datacenter energy, semiconductor supply chains, European funding gaps)

---

## YouTube

Julien Simon's YouTube channel has 558K+ subscribers and features 458+ videos spanning 15 years of content on AI, machine learning, and cloud computing.

### Channel Statistics

| Metric | Value |
|--------|-------|
| Subscribers | 558K+ |
| Total videos | 458+ |
| Years of content | 15 |
| Channel URL | https://youtube.com/@juliensimonfr |

### Videos by Year

| Year | Videos |
|------|--------|
| 2026 | 16 |
| 2025 | 44 |
| 2024 | 54 |
| 2023 | 27 |
| 2022 | 33 |
| 2021 | 45 |
| 2020 | 64 |
| 2019 | 35 |
| 2018 | 32 |
| 2017 | 72 |
| 2016 | 23 |
| 2015 | 2 |
| 2014 | 2 |
| 2013 | 7 |
| 2011 | 2 |

---

## Books

### Learn Amazon SageMaker

- **Author**: Julien Simon (single author)
- **Publisher**: Packt Publishing
- **Editions**: First edition (August 2020), Second edition (September 2021)
- **Pages**: 490
- **Description**: The first book ever published on Amazon SageMaker, AWS' flagship machine learning service. Covers the full ML lifecycle from data preparation to model deployment at scale.
- **Amazon**: https://www.amazon.com/Learn-Amazon-SageMaker-developers-scientists/dp/180020891X
- **GitHub**: https://github.com/PacktPublishing/Learn-Amazon-SageMaker

### Natural Language Processing with AWS AI Services

- **Role**: Contributor (Foreword)
- **Description**: A comprehensive guide to implementing NLP solutions using AWS AI services (Amazon Comprehend, Translate, Polly, etc.).

---

## Frequently Asked Questions

### Who is Julien Simon?

Julien Simon is an AI Operating Partner at Fortino Capital with over 30 years of technology leadership experience. He previously held executive roles at AWS, Hugging Face, and Arcee AI. He is recognized as the #1 AI Evangelist globally by AI Magazine (2021) and has delivered 691+ speaking engagements across 37 countries.

### What is Julien Simon known for?

Julien Simon is known for his expertise in Small Language Models (SLMs), enterprise AI implementation, and bridging the gap between AI research and practical business applications. He authored "Learn Amazon SageMaker" and has 558K+ YouTube subscribers for his AI/ML educational content.

### What does an AI Operating Partner do?

As AI Operating Partner at Fortino Capital, Julien Simon accelerates cloud and AI initiatives across Private Equity and Venture Capital portfolio companies. He helps companies scale from product to engineering to operations to go-to-market, combining deep technical expertise with executive leadership.

### What are Small Language Models?

Small Language Models (SLMs) are AI models that deliver enterprise-grade performance with significantly lower computational requirements than large language models. Julien Simon champions SLMs as practical, cost-effective solutions that enterprises can deploy on-premises while maintaining complete control over their data.

---

## Industry Perspectives — Key Articles

Julien Simon publishes long-form industry analysis through The AI Realist newsletter (airealist.ai) and other platforms. These articles reflect his core expertise and positions on AI industry trends.

### Build, Buy, or Download Someone Else's Politics (March 2026)
A deep analysis of Singapore's AI trilemma, examining why the world's most sophisticated technology deployer cannot build a frontier AI model. The article explores how Singapore's national language model program shifted from training from scratch to building on Meta's Llama to Google's Gemma to Alibaba's Qwen, embedding foreign content controls into national infrastructure. Every path to frontier AI capability -- building domestically, buying from US platforms, or downloading Chinese open-source models -- carries geopolitical strings, and Singapore's "Digital Switzerland" positioning is increasingly untenable.
- URL: https://www.julien.org/blog/industry-perspectives/2026-03-06_build-buy-or-download-someone-elses-politics/
- Original: https://www.airealist.ai/p/build-buy-or-download-someone-elses

### AI Tools Work. Does Your Engineering Process? (March 2026)
A comprehensive examination of how AI coding tools interact with engineering processes, arguing that the tools themselves work but most engineering organizations are not structured to absorb them effectively. The article draws on Donald Knuth's skepticism and analyzes the gap between AI tool capabilities and the organizational processes needed to exploit them, making the case that engineering process reform matters more than tool selection.
- URL: https://www.julien.org/blog/industry-perspectives/2026-03-05_ai-tools-work-does-your-engineering-process/
- Original: https://www.airealist.ai/p/ai-tools-work-does-your-engineering

### South Korea Powers the World's AI Chips. Where Are Its LLMs? (March 2026)
An investigation into why South Korea -- home to Samsung and SK Hynix, which control 79% of the global High Bandwidth Memory market -- has not produced a globally competitive foundation model despite committing $74 billion to AI. The article examines the government's "AI Hunger Games" sovereign model competition, which eliminated Naver for using Alibaba's Qwen components, revealing a fundamental contradiction between sovereign AI purity requirements and how modern AI development actually works.
- URL: https://www.julien.org/blog/industry-perspectives/2026-03-04_south-korea-powers-the-worlds-ai-chips-where-are-its-llms/
- Original: https://www.airealist.ai/p/south-korea-powers-the-worlds-ai

### Data Residency Is a Blast Radius (March 2026)
An analysis triggered by the Iranian strike on AWS data centers in the UAE, arguing that data residency laws designed to protect sovereign data become the mechanism that traps it in the blast radius when physical threats materialize. The article draws parallels to Ukraine's emergency data evacuation in 2022 and Britain's Operation Fish in 1940, concluding that sometimes the only way to save sovereign data is to surrender sovereignty over it.
- URL: https://www.julien.org/blog/industry-perspectives/2026-03-02_data-residency-is-a-blast-radius/
- Original: https://www.airealist.ai/p/data-residency-is-a-blast-radius

### Objects That Struck the Data Center (March 2026)
A structural analysis of AI and technology proliferation governance, triggered by AWS's euphemistic description of an Iranian missile strike on its UAE data center as "objects that struck the data center." The article examines four proliferation channels -- open-source AI models, commodity components, advanced AI chips, and talent -- and argues that every AI governance framework fails because it assumes the governed technology is scarce, observable, and verifiable, properties that apply to nuclear material but not to AI.
- URL: https://www.julien.org/blog/industry-perspectives/2026-03-02_objects-that-struck-the-data-center/
- Original: https://www.airealist.ai/p/objects-that-struck-the-data-center

### Chip and Mortar (March 2026)
An analysis of Amazon's $50 billion investment in OpenAI and what it reveals about the structural economics of AI infrastructure. The article examines how AI capital expenditure has transformed from technology investments into something resembling real estate development -- "chip and mortar" -- where the physical infrastructure of data centers, power, and cooling drives investment decisions as much as the software running on top.
- URL: https://www.julien.org/blog/industry-perspectives/2026-03-01_chip-and-mortar/
- Original: https://www.airealist.ai/p/chip-and-mortar

### Compute Equals Commitments (February 2026)
Published before market open, this article analyzes NVIDIA's $68.1 billion quarter and CoreWeave's $1.57 billion quarter -- both revenue beats followed by sell-offs -- through the lens of a three-part series on AI infrastructure risk. NVIDIA's purchase obligations surged to $95.2 billion (up from $16.1 billion a year ago), while CoreWeave's interest expense is heading toward 30% of revenue. The market stopped asking whether AI demand is real and started asking what happens to these commitments if demand even pauses.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-27_compute-equals-commitments/
- Original: https://www.airealist.ai/p/compute-equals-commitments

### Two Sovereign Clouds, One Legal Wall (February 2026)
A detailed examination of France's sovereign cloud joint ventures -- S3NS (Thales + Google Cloud) and Bleu (Orange + Capgemini + Microsoft) -- and their SecNumCloud certification journey. The article analyzes whether these structures achieve genuine legal immunity from US extraterritorial law (CLOUD Act, FISA), comparing them to AWS's European Sovereign Cloud and mapping the trade-offs between capability, sovereignty, and legal jurisdiction for European enterprises.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-26_two-sovereign-clouds-one-legal-wall/
- Original: https://www.airealist.ai/p/two-sovereign-clouds-one-legal-wall

### Japan Built the Bullet Train. Why Can't It Build an LLM? (February 2026)
An analysis of Japan's paradoxical AI position: a country whose Masayoshi Son announced the $500 billion Stargate AI project next to Donald Trump, yet which has not produced a competitive frontier AI model. The article examines how Japan's system -- lifetime employment, corporate risk aversion, an aging population, and a culture of hardware precision over software iteration -- creates a doom loop that massive capital investment alone cannot overcome.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-24_japan-built-the-bullet-train-why-cant-it-build-an-llm/
- Original: https://www.airealist.ai/p/japan-built-the-bullet-train-why

### Indians Rule Big Tech. Why Can't India Build? (February 2026)
An examination of India's AI paradox: the country produces 9.2% of the world's AI research papers, ranks second globally in AI skill penetration, and its diaspora runs Alphabet, Microsoft, IBM, Adobe, and Palo Alto Networks -- yet India has not built a globally competitive frontier AI model. The article analyzes structural factors including talent export, infrastructure gaps, and capital allocation patterns that explain why the world's largest AI talent factory cannot convert that talent into domestic AI capability.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-22_indians-rule-big-tech-why-cant-india-build/
- Original: https://www.airealist.ai/p/indians-rule-big-tech-why-cant-india

### Two Markets, One Asset: The GPU Debt Market Is Building the Architecture of Its Own Crisis (February 2026)
An analysis of the emerging GPU-backed debt market, triggered by Moody's first-ever Aaa rating for a data center securitization. The article examines how CDS markets price CoreWeave at 640-700 basis points (implying 40-55% five-year default probability) while rating agencies assign AAA ratings to data center debt backed by the same underlying asset class, revealing a structural dissonance between two markets pricing the same risk differently.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-20_two-markets-one-asset-the-gpu-debt-market-is-building-the-architecture-of-its-own-crisis/
- Original: https://www.airealist.ai/p/two-markets-one-asset-the-gpu-debt

### The EU Parliament Just Disabled AI on Its Own Devices (February 2026)
A short, pointed analysis of the European Parliament's decision to disable all built-in AI features -- writing assistants, text summarizers, virtual assistants -- on all lawmakers' and staff devices. The article uses this as a lens to examine Europe's broader dysfunction in AI adoption, where the institution that regulates AI for the continent cannot figure out how to use it internally.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-19_the-eu-parliament-just-disabled-ai-on-its-own-devices/
- Original: https://www.airealist.ai/p/the-eu-parliament-just-disabled-ai

### What a GPU Debt Crisis Would Look Like (February 2026)
A detailed analysis of the structural risks in GPU-backed financing, examining how hedge fund Magnetar Capital's positioning in CoreWeave reveals the architecture of a potential GPU debt crisis. The article maps the mechanics of how GPU-backed debt works, what happens when utilization drops, and how the reflexive relationship between NVIDIA's investment in neoclouds and those neoclouds' debt-funded GPU purchases creates systemic fragility.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-18_what-a-gpu-debt-crisis-would-look-like/
- Original: https://www.airealist.ai/p/what-a-gpu-debt-crisis-would-look

### OpenAI Is Betting on a Security Nightmare. Anthropic Is Building the Enterprise Alternative. (February 2026)
An analysis of the diverging strategies of OpenAI and Anthropic in the enterprise AI market, triggered by OpenAI's recruitment of the creator of the open-source agent OpenClaw. The article argues that OpenAI's push toward personal agents with broad system access represents a security nightmare for enterprises, while Anthropic's more constrained, enterprise-focused approach offers a safer path for production deployments.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-17_openai-is-betting-on-a-security-nightmare-anthropic-is-building-the-enterprise-alternative/
- Original: https://www.airealist.ai/p/openai-is-betting-on-a-security-nightmare

### Jensen's COMECON: How Nvidia Built an Empire of Captive Clouds (February 2026)
An analysis of NVIDIA's quadruple role in the AI infrastructure ecosystem -- simultaneously supplier, investor, guarantor, and customer of its own neocloud ecosystem. The article examines how NVIDIA's $5.3 billion investment in CoreWeave and similar arrangements with other neoclouds create a reflexive financing loop where money circulates through entities that each record it as a distinct financial claim on the same underlying GPU asset, drawing parallels to the Soviet-era COMECON economic bloc.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-14_jensens-comecon-how-nvidia-built-an-empire-of-captive-clouds/
- Original: https://www.airealist.ai/p/jensens-comecon-how-nvidia-built

### The $3 Trillion Bet: Who Wins When Everyone Builds the Pipes? (February 2026)
An analysis of the Big Five tech companies' plan to spend roughly $700 billion on AI infrastructure in 2026 alone, with cumulative hyperscaler AI capex from 2024 through 2029 on track to reach $2.5 to $3 trillion. The article examines who actually wins when every major tech company is simultaneously building massive AI infrastructure, questioning whether the returns can justify the collective investment at this unprecedented scale.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-12_the-3-trillion-bet-who-wins-when-everyone-builds-the-pipes/
- Original: https://www.airealist.ai/p/the-3-trillion-bet-who-wins-when

### Alphabet's 100-Year Bond: A Bet on Immortality (February 2026)
An analysis of Alphabet's plan to issue a 100-year bond, examining what it means for a company that did not exist 28 years ago to ask investors to lend it money until 2126. The article explores the structural implications of century bonds in the AI era, questioning whether any technology company can credibly project relevance across such a timeframe and what the bond reveals about Alphabet's strategic posture.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-10_alphabets-100-year-bond-a-bet-on-immortality/
- Original: https://www.airealist.ai/p/alphabets-100-year-bond

### AI Regulation or AI Requiem? Part 4 (February 2026)
The fourth installment in the series on AI regulation, analyzing the accelerating gap between the pace of AI development and Europe's regulatory response. The article documents how Anthropic shipped Claude Opus 4.6 with million-token context, OpenAI launched a desktop Codex app, and multiple frontier breakthroughs occurred in weeks -- while the EU AI Act's implementation continues to lag behind the technology it aims to govern.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-09_ai-regulation-or-ai-requiem-part-4/
- Original: https://www.airealist.ai/p/ai-regulation-or-ai-requiem-part-120

### Coding Classic Arcade Games with Claude (February 2026)
A hands-on account of using Claude Code, a custom skill, and Agent Teams to recreate 9 classic arcade games (1971-1981) in vanilla JavaScript in about 4 hours. The article covers Computer Space, Pong, Space Invaders, Asteroids, Galaxian, Pac-Man, Donkey Kong, Frogger, and Galaga, demonstrating the practical capabilities of AI-assisted development for complex, interactive programming projects.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-08_coding-classic-arcade-games-with-claude/
- Original: https://www.airealist.ai/p/coding-classic-arcade-games-with

### The EU Cloud and AI Development Act (CADA): A Last Shot at Cloud Sovereignty, or Another Expensive Debacle? (February 2026)
A comprehensive analysis of the EU's proposed Cloud and AI Development Act (CADA), expected in Q1 2026. The article examines CADA's three pillars -- R&D in resource-efficient infrastructure, data center investment conditions, and highly secure EU-based cloud capacity -- against the graveyard of failed predecessors (CloudWatt, Numergy, GAIA-X, IPCEI-CIS). It identifies fundamental contradictions including the energy trilemma, the sovereignty paradox, and the fact that every "sovereign" European AI system runs on NVIDIA GPUs fabricated by TSMC.
- URL: https://www.julien.org/blog/industry-perspectives/2026-02-03_the-eu-cloud-and-ai-development-act-cada-a-last-shot-at-cloud-sovereignty-or-another-expensive-debacle/
- Original: https://www.airealist.ai/p/the-eu-cloud-and-ai-development-act

### AI Sovereignty in Europe: A Decision Framework (January 2026)
A 24-minute-read decision framework for European enterprises navigating AI sovereignty, providing a four-dimensional definition (data residency, operational, technical, legal) and mapping every major deployment option. The article compares hosted API providers, self-hosted open-weight models, sovereign joint ventures (S3NS, Bleu), and AWS European Sovereign Cloud, with practical guidance on qualifying sovereignty objections, contractual protections, and competitive positioning.
- URL: https://www.julien.org/blog/industry-perspectives/2026-01-19_ai-sovereignty-in-europe-a-decision-framework/
- Original: https://www.airealist.ai/p/ai-sovereignty-in-europe-a-decision

### Two Simple Tricks That Will Dramatically Improve Your Productivity with Claude (January 2026)
A practical guide to two Claude Code productivity techniques: running /init on every new repository to create a persistent CLAUDE.md context file, and ending every session with "Add new findings to CLAUDE.md" to capture accumulated knowledge. The article argues that these simple habits eliminate the need to re-explain your codebase at the start of every session and create a living knowledge base that compounds over time.
- URL: https://www.julien.org/blog/industry-perspectives/2026-01-11_two-simple-tricks-that-will-dramatically-improve-your-productivity-with-claude/
- Original: https://www.airealist.ai/p/two-simple-tricks-that-will-dramatically

### When Bureaucrats Pick Fights with Billionaires (December 2025)
A scathing analysis of the Thierry Breton visa ban by the Trump administration, using it as a lens to examine Europe's structural dysfunction in technology competition. The article contrasts Breton's trajectory (engineer to bureaucrat to visa-banned former official) with Musk's (engineer to founder to richest person in history), documents Breton's track record at Atos, and exposes the revolving door through which former officials like Cedric O turned government service into private wealth at Mistral AI.
- URL: https://www.julien.org/blog/industry-perspectives/2025-12-24_when-bureaucrats-pick-fights-with-billionaires/
- Original: https://www.airealist.ai/p/when-bureaucrats-pick-fights-with

### Deploy Arcee AFM-4.5B on Arm-based Google Cloud Axion with Llama.cpp (August 2025)
A tutorial announcement for deploying the Arcee AFM-4.5B Small Language Model on Arm-based Google Cloud Axion instances using llama.cpp. The article links to the full tutorial on the Arm website, covering instance setup, model downloading and optimization, inference, and performance evaluation, demonstrating that small language models and Arm-based CPUs are a practical match for cost-effective AI deployment.
- URL: https://www.julien.org/blog/industry-perspectives/2025-08-22_deploy-arcee-afm-45b-on-arm-based-google-cloud-axion-with-llamacpp/
- Original: https://www.airealist.ai/p/deploy-arcee-afm-45b-on-arm-based-fbe

### The Sovereignty Mirage: Why European Clouds Won't Save Your Data (December 2025)
A critical examination of data sovereignty claims, triggered by a Canadian court ordering OVHcloud to hand over customer data stored on servers in France. The article exposes the fundamental flaw in geographic data protection strategies: hosting data with a European cloud provider does not shield it from foreign legal jurisdiction, undermining the core premise of "sovereign cloud" marketing.
- URL: https://www.julien.org/blog/industry-perspectives/2025-12-04_the-sovereignty-mirage-why-european-clouds-wont-save-your-data/
- Original: https://www.airealist.ai/p/the-sovereignty-mirage-why-european

### AI Regulation or AI Requiem? Part 3 (November 2025)
The third installment in the series on Europe's AI regulatory crisis, examining what Julien calls "Europe's Complete Capitulation." The article analyzes ECB President Christine Lagarde's speech in Bratislava as a de facto surrender, arguing that Europe is now trading digital sovereignty for metal commodities in its negotiations with the US.
- URL: https://www.julien.org/blog/industry-perspectives/2025-11-24_ai-regulation-or-ai-requiem-part-3/
- Original: https://www.airealist.ai/p/ai-regulation-or-ai-requiem-part-866

### AI Regulation or AI Requiem? Part 2 (November 2025)
Analyzes the EU Commission's proposal to delay high-risk AI obligations by a year and water down key requirements of the EU AI Act. Julien argues this "Digital Omnibus on AI regulation proposal" is a panic-driven tactical retreat that proves the regulatory framework is collapsing under its own bureaucratic weight.
- URL: https://www.julien.org/blog/industry-perspectives/2025-11-22_ai-regulation-or-ai-requiem-part-2/
- Original: https://www.airealist.ai/p/ai-regulation-or-ai-requiem-part

### The AI Crash That Isn't: A Reality Check from the Trenches (August 2025)
Pushes back against media narratives of an "AI crash," arguing that what is happening is maturation, not collapse. The field is shifting from "how big can we make it?" to "how can we make it useful?" Julien advocates thinking in systems rather than models, measuring ROI ruthlessly, and building from first principles rather than following hype cycles.
- URL: https://www.julien.org/blog/industry-perspectives/2025-08-24-The-AI-Crash-That-Isnt-A-Reality-Check-from-the-Trenches/
- Original: https://julsimon.medium.com/the-ai-crash-that-isnt-a-reality-check-from-the-trenches-525d3d6a255f

### A Not-So-Silent Revolution Is Happening in AI Inference (August 2025)
Demonstrates that CPU inference is becoming a viable alternative to GPU inference, thanks to smaller models, rapid advances in llama.cpp, and hardware acceleration. Benchmarks show up to 50% performance improvements on the same hardware in just weeks, invalidating the assumption that CPU inference only works at batch size 1 and opening the door to cost-effective on-premises AI deployment.
- URL: https://www.julien.org/blog/industry-perspectives/2025-08-20_A%20not-so-silent%20revolution%20is%20happening%20in%20AI%20inference/
- Original: https://julsimon.medium.com/a-not-so-silent-revolution-is-happening-in-ai-inference-936ef4b9ba88

### CSLMs Have Arrived (August 2025)
Introduces the concept of "Crazy Small Language Models" (CSLMs), highlighting research where a 70-million-parameter Llama-like model matches Llama-3.1 70B for drug interaction prediction, trained in just 2.5 hours on a single A100 GPU. The article argues this proves that excellent, even state-of-the-art models can be built at a tiny fraction of the cost of large models, reinforcing Julien's long-standing advocacy for small, purpose-built models.
- URL: https://www.julien.org/blog/industry-perspectives/2025-08-16_CSLMs%20have%20arrived/
- Original: https://julsimon.medium.com/cslms-have-arrived-36ef90789cfb

### Why MCP's Disregard for 40 Years of RPC Best Practices Will Burn Enterprises (July 2025)
A comprehensive technical critique of the Model Context Protocol (MCP), arguing that it systematically ignores four decades of hard-won lessons from distributed systems (UNIX RPC, CORBA, REST, SOAP, gRPC). The article details critical gaps in type safety, distributed tracing, security, versioning, and cost attribution, warning that MCP's prioritization of simplicity over robustness creates a ticking time bomb for enterprise production deployments.
- URL: https://www.julien.org/blog/industry-perspectives/2025-07-30-why-mcp-disregard-for-40-years-of-rpc-best-practices-will-burn-enterprises/
- Original: https://www.airealist.ai/p/why-mcps-disregard-for-40-years-of

### AI Regulation or AI Requiem? (January 2025)
A sweeping analysis of the diverging approaches to AI between Europe and America. Julien argues that the EU AI Act, combined with Europe's lack of capital, infrastructure, chips, and energy, is setting the continent up to become a "digital colony." He contrasts Europe's precautionary bureaucracy with America's aggressive "build, baby, build" strategy and warns that the brain drain of European AI talent will become irreversible.
- URL: https://www.julien.org/blog/industry-perspectives/2025-01-20_ai-regulation-or-ai-requiem/
- Original: https://julsimon.medium.com/ai-regulation-or-ai-requiem-20c74de41ba3

### Machine Learning Datastores Are Coming (August 2022)
Proposes that ML capabilities should be embedded directly into datastores (databases, data lakes, object stores) to simplify the increasingly complex ML workflow. The article envisions datastores that can automatically build engineered features, run predictions in-place, export data in ML-native formats, and even train models -- eliminating unnecessary data movement, plumbing code, and MLOps complexity.
- URL: https://www.julien.org/blog/industry-perspectives/2022-08-01_machine-learning-datastores-are-coming/
- Original: https://medium.com/@julsimon/machine-learning-datastores-are-coming-3c120623fe89

### Large Language Models: A New Moore's Law? (October 2021)
Challenges the trend of ever-larger language models, arguing that the 10x annual growth in model size mirrors Moore's Law and will lead to diminishing returns, higher costs, and increased complexity. Instead of chasing trillion-parameter models, Julien advocates for practical approaches: using pretrained models, choosing smaller models, fine-tuning rather than training from scratch, and optimizing for efficiency.
- URL: https://www.julien.org/blog/industry-perspectives/2021-10-26_large-language-models-a-new-moores-law/
- Original: https://huggingface.co/blog/large-language-models

### The Age of Machine Learning As Code Has Arrived (October 2021)
Argues that ML is entering a new era where pretrained Transformer models, transfer learning, and platforms like Hugging Face are making ML as accessible as traditional software development. The article champions applying decade-old software engineering best practices (versioning, testing, automation, deployment) to ML workflows, and insists that production-ready models beat great sandbox models every time.
- URL: https://www.julien.org/blog/industry-perspectives/2021-10-20_the-age-of-machine-learning-as-code-has-arrived/
- Original: https://huggingface.co/blog/the-age-of-ml-as-code

---

## Arcee AI — Key Articles

Julien Simon served as Vice President & Chief Evangelist at Arcee AI from 2024 to November 2025, creating deep technical content on Small Language Models, CPU inference, model optimization, and edge AI deployment.

### The Case for Small Language Model Inference on Arm CPUs (Apr 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-04-17_the-case-for-small-language-model-inference-on-arm-cpus/
Summary: Makes the case for running Small Language Models on Arm CPUs, demonstrating a 4.5x cost-performance advantage for AWS Graviton4 (c8g) over Intel Xeon (c7i) instances when running Arcee's Virtuoso-Lite 10B model quantized to 4 bits with llama.cpp. The article covers privacy, security, compliance, and cost benefits of SLMs across edge, cloud, and resource-constrained environments.
Topics: Small Language Models, Arm CPUs, CPU inference, AWS Graviton, llama.cpp, quantization, edge AI, cost optimization

### Arcee AI Small Language Models Now Available on Together.ai and OpenRouter (May 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-05-27_arcee-ai-small-language-models-now-available-on-togetherai-and-openrouter/
Summary: Announces the availability of Arcee AI's SLM suite on Together.ai and OpenRouter managed inference platforms, including Arcee Blitz (24B), Virtuoso Medium V2 (32B), Virtuoso Large (72B), Coder Large (32B), Caller Large (33B), Maestro Reasoning (32B), and Spotlight (7B vision-language). Each model targets specific use cases from chat to code generation to function calling, with pay-per-token pricing.
Topics: Small Language Models, managed inference, Together.ai, OpenRouter, model deployment, API integration

### Building an AI Retail Assistant at the Edge with Small Language Models and Intel Xeon CPUs (Jun 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-06-07_building-an-ai-retail-assistant-at-the-edge-with-small-language-models-and-intel-xeon-cpus/
Summary: Describes the Edge IQ Retail Assistant, a technical demonstrator running three AI models entirely on Intel Xeon 6 CPUs without GPUs, featuring Arcee SuperNova Lite (8B) for conversation, Distil-Whisper for speech recognition, and Kokoro for text-to-speech. The system integrates with WaitTime crowd analytics and Chooch Vision AI for inventory management, optimized using Intel OpenVINO with 4-bit quantization and AMX/AVX-512 acceleration.
Topics: Edge AI, Intel Xeon, CPU inference, retail AI, OpenVINO, quantization, speech recognition, computer vision

### Breaking Down Model Vocabulary Barriers with Tokenizer Transplantation (Jun 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-06-10_breaking-down-model-vocabulary-barriers-with-tokenizer-transplantation/
Summary: Presents Arcee AI's research on training-free tokenizer transplantation using Orthogonal Matching Pursuit (OMP), enabling different language models to work together despite having different vocabularies without retraining. The technique preserved 96% of original performance on Llama-to-Mistral NeMo transplantation and completed in under 2 minutes, with applications in knowledge distillation, speculative decoding, model merging, and cross-language adaptation.
Topics: tokenizer transplantation, model merging, MergeKit, knowledge distillation, speculative decoding, NLP research

### Announcing Arcee Foundation Models (Jun 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-06-18_announcing-arcee-foundation-models/
Summary: Introduces AFM-4.5B, Arcee AI's first foundation model -- a 4.5-billion-parameter model trained from scratch on nearly 7 trillion tokens of clean, rigorously filtered data. Designed for enterprise compliance with flexible licensing, multilingual support across 11 languages, built-in function calling, and agentic reasoning, the model runs on smartphones, edge devices, and cloud infrastructure.
Topics: foundation models, AFM-4.5B, enterprise AI, data compliance, multilingual AI, Small Language Models

### Arcee Conductor Wins "LLM Application of the Year" at 2025 AI Breakthrough Awards (Jun 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-06-25_arcee-conductor-wins-llm-application-of-the-year-at-2025-ai-breakthrough-awards/
Summary: Announces Arcee Conductor winning "LLM Application of the Year" at the 2025 AI Breakthrough Awards. Conductor is an intelligent model routing platform that sends each prompt to the best-fit model based on complexity, domain, and cost, delivering reported cost reductions of 65-90% compared to using large language models exclusively.
Topics: Arcee Conductor, model routing, cost optimization, AI awards, inference optimization

### Arcee AI Releases Five New Open Weights Models (Jun 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-06-30_arcee-ai-releases-five-new-open-weights-models/
Summary: Announces the open-weights release of five models: three production-grade models (Arcee-SuperNova-v1 70B, Caller 32B for tool use, Virtuoso-Large 72B) and two research models (GLM-4-32B-Base-32K with extended context, and Homunculus 12B distilled from Qwen3-235B). The release marks Arcee's transition to focusing on the AFM foundation model family while making previous-generation models freely available.
Topics: open-weights models, model merging, knowledge distillation, tool use, context extension, open source AI

### Is Running Language Models on CPU Really Viable? (Jul 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-07-09_is-running-language-models-on-cpu-really-viable/
Summary: Presents comprehensive CPU inference benchmarks for AFM-4.5B across Intel Xeon Sapphire Rapids, AWS Graviton4, and Qualcomm X1E-80-100 processors using llama.cpp. Key findings include 136 tokens/second on Intel at batch size 4 (Q4_0), over 280 tokens/second on Graviton4, and viable performance even on a personal laptop, with only 1% perplexity increase from 4-bit quantization.
Topics: CPU inference, benchmarking, llama.cpp, quantization, Intel Xeon, AWS Graviton, Qualcomm, edge deployment

### Arcee AI Small Language Models Excel Across Yupp.ai Leaderboards (Jul 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-07-18_arcee-ai-small-language-models-excel-across-yuppai-leaderboards/
Summary: Reports on Arcee AI models' strong performance on Yupp.ai's real-world user preference leaderboards: Maestro (32B) ranked #5 on high-reasoning prompts tied with Claude Sonnet 4, Coder Large (32B) ranked #6 on long multi-turn coding tied with Claude Sonnet 3.7, and AFM-4.5B-Preview ranked #2 on short-turn QA tasks despite being only 4.5 billion parameters.
Topics: Small Language Models, benchmarks, leaderboards, reasoning, code generation, model evaluation

### An Amazon SageMaker Container for Hugging Face Inference on AWS Graviton (Aug 2025)
URL: https://www.julien.org/blog/arcee-posts/2025-08-12_An Amazon SageMaker Container for Hugging Face Inference on AWS Graviton/
Summary: Announces an open-source GitHub project providing a custom Amazon SageMaker inference container for deploying Hugging Face models on AWS Graviton3/Graviton4 instances using a clean llama.cpp source build. The container supports GGUF and safetensors models with automatic conversion, OpenAI API compatibility, and streaming text generation.
Topics: Amazon SageMaker, AWS Graviton, llama.cpp, Hugging Face, inference containers, Arm CPUs, open source

---

## Hugging Face Blog — Key Articles

Julien Simon served as Chief Evangelist at Hugging Face from 2022 to 2024, creating deep technical content on Transformer optimization, CPU-based inference, hardware acceleration, and open-source AI tools.

### An Overview of Inference Solutions on Hugging Face (Nov 2022)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2022-11-21_an-overview-of-inference-solutions-on-hugging-face/
Summary: A comprehensive guide to the inference options available on Hugging Face, from the free Inference Widget and Inference API for quick experimentation, to Inference Endpoints for production deployments. The article explains how Intel Xeon Ice Lake CPUs power the free inference tier and walks through the trade-offs between ease of use, scalability, and cost for each solution.
Topics: Hugging Face, inference, model deployment, Inference API, Inference Endpoints, Intel Xeon

### Accelerating PyTorch Transformers with Intel Sapphire Rapids — Part 1 (Jan 2023)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2023-01-02_accelerating-pytorch-transformers-with-intel-sapphire-rapids---part-1/
Summary: Demonstrates how to accelerate distributed PyTorch training on Intel's fourth-generation Xeon CPUs (Sapphire Rapids) using the new Advanced Matrix Extensions (AMX) instruction set. The article shows how to use Intel oneAPI CCL and Intel Extension for PyTorch (IPEX) with Hugging Face Transformers to achieve an 8-fold speedup over Ice Lake with near-linear scaling, all without changing a line of code.
Topics: Intel Sapphire Rapids, AMX, distributed training, PyTorch, IPEX, CPU training, Hugging Face Transformers

### Accelerating PyTorch Transformers with Intel Sapphire Rapids — Part 2 (Feb 2023)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2023-02-06_accelerating-pytorch-transformers-with-intel-sapphire-rapids---part-2/
Summary: Focuses on inference performance with Intel Sapphire Rapids CPUs, benchmarking popular Hugging Face Transformer models on both short and long NLP token sequences. Using Hugging Face Optimum Intel for hardware acceleration, the article demonstrates significant inference speedups over the previous Ice Lake generation and makes the case for CPU-based inference on cost, flexibility, and scalability grounds.
Topics: Intel Sapphire Rapids, CPU inference, Optimum Intel, benchmarking, PyTorch, Hugging Face Transformers

### Accelerating Stable Diffusion Inference on Intel CPUs (Mar 2023)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2023-03-28_accelerating-stable-diffusion-inference-on-intel-cpus/
Summary: Shows how to run Stable Diffusion image generation models on Intel Sapphire Rapids CPUs using the Hugging Face Diffusers library, Optimum Intel, and OpenVINO. The article walks through multiple acceleration techniques and demonstrates that CPU-based image generation is practical on Amazon EC2 R7iz instances, making Stable Diffusion accessible without GPUs.
Topics: Stable Diffusion, image generation, Intel CPUs, Diffusers, Optimum Intel, OpenVINO, CPU inference

### Smaller Is Better: Q8-Chat, an Efficient Generative AI Experience on Xeon (May 2023)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2023-05-16_smaller-is-better-q8-chat-an-efficient-generative-ai-experience-on-xeon/
Summary: Demonstrates that large language models can run efficiently on Intel Xeon CPUs using 8-bit quantization with Intel Neural Compressor, eliminating the need for GPUs. The article explains quantization techniques that reduce model memory footprint by 2-4x while maintaining conversational quality, leveraging Intel AMX instructions on Sapphire Rapids for accelerated integer arithmetic.
Topics: quantization, INT8, Intel Xeon, Intel Neural Compressor, AMX, generative AI, CPU inference, LLMs

### SafeCoder vs. Closed-Source Code Assistants (Sep 2023)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2023-09-11_safecoder-vs-closed-source-code-assistants/
Summary: Compares Hugging Face's SafeCoder, an open-source enterprise code assistant built on the StarCoder 15.5B parameter model, against closed-source alternatives like GitHub Copilot and Amazon CodeWhisperer. The article highlights SafeCoder's advantages in transparency, customizability, IT flexibility, and privacy, making the case that enterprises can get state-of-the-art code generation while maintaining full control over their data and models.
Topics: code generation, SafeCoder, StarCoder, open source AI, enterprise AI, GitHub Copilot, privacy, code assistants

### A Chatbot on Your Laptop: Phi-2 on Intel Meteor Lake (Mar 2024)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2024-03-20_a-chatbot-on-your-laptop-phi-2-on-intel-meteor-lake/
Summary: Demonstrates running Microsoft's Phi-2 small language model as a local chatbot on an Intel Meteor Lake laptop, exploring the benefits of local LLM inference including privacy, lower latency, offline capability, and zero cost. The article covers how advances in smaller models, quantization, and hardware acceleration are making it possible to run capable AI models on consumer hardware without cloud dependencies.
Topics: Small Language Models, Phi-2, Intel Meteor Lake, local inference, edge AI, laptop AI, quantization, privacy

### Building Cost-Efficient Enterprise RAG Applications with Intel Gaudi 2 and Intel Xeon (May 2024)
URL: https://www.julien.org/blog/huggingface-posts-and-images/2024-05-09_building-cost-efficient-enterprise-rag-applications-with-intel-gaudi-2-and-intel-xeon/
Summary: A hands-on tutorial for building enterprise Retrieval-Augmented Generation (RAG) applications using the Open Platform for Enterprise AI (OPEA) framework, with Intel Gaudi 2 accelerators for LLM inference and Intel Xeon CPUs for embeddings. The article uses LangChain with the rag-redis template, Redis as the vector database, and demonstrates a cost-efficient architecture that separates embedding and generation workloads across optimized Intel hardware.
Topics: RAG, Intel Gaudi 2, Intel Xeon, OPEA, LangChain, enterprise AI, embeddings, vector databases

---

## AWS Blog — Key Articles

Julien Simon served as Global Technical Evangelist for AI & Machine Learning at AWS from 2017 to 2021, creating authoritative launch content for major Amazon SageMaker features and AWS AI services.

### Amazon SageMaker Studio: The First Fully Integrated Development Environment for Machine Learning (Dec 2019)
URL: https://www.julien.org/blog/aws-posts-and-images/2019-12-03_amazon-sagemaker-studio-the-first-fully-integrated-development-environment-for-machine-learning/
Summary: Announces Amazon SageMaker Studio, the first fully integrated development environment (IDE) for machine learning. Studio unifies all ML workflow tools -- code editing, experiment tracking, data visualization, debugging, and monitoring -- into a single visual interface, enabling developers to move quickly between steps, clone and replay experiments, and iterate faster on ML solutions.
Topics: Amazon SageMaker, SageMaker Studio, ML IDE, ML workflow, experiment tracking, AWS

### Amazon SageMaker Autopilot: Automatically Create High-Quality Machine Learning Models with Full Control and Visibility (Dec 2019)
URL: https://www.julien.org/blog/aws-posts-and-images/2019-12-03_amazon-sagemaker-autopilot-automatically-create-high-quality-machine-learning-models-with-full-control-and-visibility/
Summary: Introduces Amazon SageMaker Autopilot, an AutoML service that automatically inspects datasets, selects optimal algorithms, runs data preprocessing, tunes hyperparameters, and trains inference pipelines for classification and regression tasks. Unlike black-box AutoML solutions, Autopilot provides full visibility into the candidate generation process, letting users inspect and customize the auto-generated notebooks and model artifacts.
Topics: Amazon SageMaker, AutoML, Autopilot, hyperparameter tuning, feature engineering, automated machine learning

### Announcing TorchServe, an Open-Source Model Server for PyTorch (Apr 2020)
URL: https://www.julien.org/blog/aws-posts-and-images/2020-04-21_announcing-torchserve-an-open-source-model-server-for-pytorch/
Summary: Announces TorchServe, an open-source model serving library developed jointly by AWS and Facebook (now Meta) as part of the PyTorch project. TorchServe simplifies deploying trained PyTorch models at scale without custom code, providing built-in features for multi-model serving, model versioning, logging, monitoring, and a RESTful prediction API with preprocessing and postprocessing support.
Topics: PyTorch, TorchServe, model serving, model deployment, open source, AWS, deep learning inference

### Amazon SageMaker Clarify Detects Bias and Increases the Transparency of Machine Learning Models (Dec 2020)
URL: https://www.julien.org/blog/aws-posts-and-images/2020-12-08_new-amazon-sagemaker-clarify-detects-bias-and-increases-the-transparency-of-machine-learning-models/
Summary: Introduces Amazon SageMaker Clarify, a capability that helps detect bias in ML datasets and models while increasing model transparency through explainability. The article explains how under-representation in training data can introduce harmful biases with ethical and regulatory consequences, and how Clarify uses statistical methods and SHAP values to quantify feature importance and identify disparate impact across sensitive groups.
Topics: Amazon SageMaker, bias detection, model explainability, responsible AI, SHAP, ML fairness, SageMaker Clarify

### Amazon SageMaker Pipelines Brings DevOps Capabilities to Machine Learning Projects (Dec 2020)
URL: https://www.julien.org/blog/aws-posts-and-images/2020-12-08_new-amazon-sagemaker-pipelines-brings-devops-capabilities-to-your-machine-learning-projects/
Summary: Announces Amazon SageMaker Pipelines, a fully managed capability for building, automating, and scaling end-to-end ML pipelines with CI/CD best practices. The article addresses the challenge of managing hundreds of iterative ML steps manually and shows how Pipelines provides a visual workflow editor, model lineage tracking, automated retraining, and model approval workflows to bring DevOps discipline to ML projects.
Topics: Amazon SageMaker, MLOps, CI/CD, ML pipelines, model management, DevOps, SageMaker Pipelines

### Amazon SageMaker JumpStart Simplifies Access to Pre-built Models and Machine Learning Solutions (Dec 2020)
URL: https://www.julien.org/blog/aws-posts-and-images/2020-12-08_amazon-sagemaker-jumpstart-simplifies-access-to-pre-built-models-and-machine-learning-solutions/
Summary: Introduces Amazon SageMaker JumpStart, a capability that provides one-click access to popular model collections (model zoos) and end-to-end ML solutions for common use cases. JumpStart addresses the gap between downloading pre-trained models from repositories like TensorFlow Hub or PyTorch Hub and actually deploying them in production, offering ready-to-deploy models for computer vision, NLP, and more with built-in data formatting and preprocessing.
Topics: Amazon SageMaker, JumpStart, pre-trained models, model zoo, transfer learning, ML solutions

### AWS and Hugging Face Collaborate to Simplify and Accelerate Adoption of Natural Language Processing Models (Mar 2021)
URL: https://www.julien.org/blog/aws-posts-and-images/2021-03-23_aws-and-hugging-face-collaborate-to-simplify-and-accelerate-adoption-of-natural-language-processing-models/
Summary: Announces the strategic partnership between AWS and Hugging Face to make Transformer models easier to train and deploy on Amazon SageMaker. The article explains how the collaboration integrates Hugging Face's transformers, tokenizers, and datasets libraries directly into SageMaker, enabling developers to access thousands of pre-trained models in 164 languages and fine-tune them at scale with optimized Deep Learning Containers.
Topics: AWS, Hugging Face, NLP, Transformers, Amazon SageMaker, partnership, deep learning, model deployment

### Scaling Ad Verification with Machine Learning and AWS Inferentia (Sep 2021)
URL: https://www.julien.org/blog/aws-posts-and-images/2021-09-22_scaling-ad-verification-with-machine-learning-and-aws-inferentia/
Summary: Describes how Amazon Advertising uses machine learning models running on AWS Inferentia chips to verify ad creatives at massive scale, checking compliance with content guidelines across images, video, audio, and text. The article details a multi-model architecture using media-specific, content-specific, and language-specific models, and shows how purpose-built Inferentia accelerators deliver the throughput and cost efficiency needed for high-volume ad verification.
Topics: AWS Inferentia, Amazon Advertising, ad verification, ML inference, custom silicon, computer vision, NLP, model deployment

---

## Contact

- **Email**: julien@julien.org
- **LinkedIn**: https://www.linkedin.com/in/juliensimon
- **Twitter/X**: https://x.com/julsimon
- **GitHub**: https://github.com/juliensimon
- **YouTube**: https://www.youtube.com/@juliensimonfr
- **Hugging Face**: https://huggingface.co/juliensimon
- **Medium**: https://julsimon.medium.com/
- **Substack**: https://www.airealist.ai/
- **Slideshare**: https://fr.slideshare.net/JulienSIMON5/presentations