Data Whisperer ♦ Analytics Specialist & Tech Enthusiast ♦ Join My #bookaweekchallenge

⭐ I have reached the maximum connection limit of 30,000 here on LinkedIn. Please follow me instead.
📚 Follow & join my #bookaweekchallenge or #bookamonthchallenge
📍 Current resident of Madrid, Spain & native of Charlotte, North Carolina, USA

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Greek-American based in Spain where I run a global data/AI business. International keynote speaker, award-winning educator and the Founder of Dare to Data, on a mission to help individuals and corporations take the next step in their data and AI journey. After building a successful career in Big Tech companies such as Google and Waze, I shifted my focus to scaling impact through education, training and product evangelism. Today, I'm trusted by an extensive client list of Fortune 500 and Big Tech organizations. Outside of my corporate work, I hold an Adjunct Faculty position at several universities where I lecture and lead programs on data and AI for business. I also serve as an instructor for LinkedIn Learning and host a podcast for EM360. I am bilingual (English-Spanish) and offer collaborations in both languages.

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I am a regular international speaker supporting all things data and AI, as well as women in STEM. Some of my latest involvements include:
● Guest appearances on more than 30 podcasts such as SuperDataScience, DataFramed, Alter Everything, Ken's Nearest Neighbors, How to Get An Analytics Job, Driven by Data, Humans of Data Science, Present Beyond Measure, LightsOnData & more.
● Interview features, guest lecturer, panelist and event host!
● Keynote speeches delivered regularly since 2018 across 20+ countries in-person, virtually spanning the globe, with audiences surpassing 3,000+. A few of my latest involvements include:
→ → Fund Summit 2025 in Luxembourg LU, "Regulating the Machine: How AI is Forcing a Global Rethink on Ethics & Control"
→ → National Analytics Summit 2025 in Dublin IE, "When Data Meets Design"
→ → CNG Global Pulp Conference 2025 in Istanbul TR, "Igniting Transformation with AI"
→ → QSP Summit 2024 in Porto PT, "Navigating Tomorrow in a Data-Driven, AI-First World"
→ → Nitto ATP Finals Customer Summit 2024 in Turin IT, "Unleashing AI's Power in Modern Manufacturing"
→ → Data Universe 2024 in NYC US, "When Data Meets Design"

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For further opportunities (podcasts, events, etc.) in my interested fields, feel free to contact me directly.

The opinions stated here are my own, not those of my employers/partners/clients.

Christina Stathopoulos, MSc

Your professional headshot is often your first impression.

On platforms like LinkedIn, it quietly answers a lot of questions for you: Are you credible? Approachable? Mine attached here is showing a subtle hint into my love for books!

There is no excuse for you to still be using that at-home selfie in bad lighting or your cropped family photo 🙄

Lately I have been experimenting with InstaHeadshots to generate AI-powered headshots. And the results are impressive! But there is a big caveat that often gets missed with these tools.

AI is only as good as the data you train it on.

If you want high quality outputs, you need high quality inputs.

When I trained my model, I used a mix of strong professional headshots and everyday photos and selfies. Different lighting, expressions, outfits and contexts.

That made all the difference in how realistic and usable my final images were.

⭐ I want to clarify that I don't think AI-generated images will replace the need for photographers. Not even close. ⭐

I fully plan to keep getting professional headshots done every two to three years. A great photographer brings expertise and quality that AI cannot do on its own.

What AI tools like this do change is SCALE.

AI now gives me access to literally HUNDREDS of additional, on brand images that I can use across platforms, talks, media and more. A quantity that would be unthinkable with a traditional photoshoot, both in terms of time and cost.

If you want to experiment with it yourself, you can try it here: https://lnkd.in/e7CnHNVU
Use code CHRISTINA15 for 15% off!

(I personally love this platform because you get a preview of your images first, and only pay once you're happy with the results.)

#artificialintelligence #generativeAI #headshots #futureofwork


💙 I partnered with InstaHeadshots because I genuinely love the product, can't wait to start using my new set of headshots and wanted to spread the word so others can try too!

🔷 TL;DR Remember that better data leads to better results. Invest in good photography. Use AI to extend it.

Data & AI Evangelist | Global Keynote Speaker & Award-Winning Educator | Making data & AI work for everyone, through a responsible lens! | Join my #bookaweekchallenge 📚

Richmond Alake is a highly experienced Machine Learning Architect and Engineer with over five years of expertise in the field. He specializes in Computer Vision and Deep Learning and has a proven track record of successfully developing and integrating deep learning models to solve a wide range of problems, such as motion detection, object detection, and pose estimation. Throughout his career, he has worked with a diverse range of clients, including large conglomerates, financial institutions, and small startups. In addition to his professional work, Richmond also serves as an AI advisor to a number of startups in the UK and the US.

With a background in building websites and mobile applications, Richmond is a firm believer in using technology to solve everyday problems. He has extensive knowledge of Machine Learning and has written over 200 articles on the subject, gaining over a million views. He was recognized as one of Medium's top AI writers in 2020/2021 and has collaborated with companies such as O'Reilly, BuiltIn and Nvidia to develop effective educational and informative learning materials on AI.

Currently, Richmond Alake is a Machine Learning Architect at Slalom Build UK. As the first hire of the machine learning practice in the UK division, he is responsible for helping organizations move from machine learning research to productionization and assisting maturing organizations in promoting AI models into existing infrastructure to drive commercial and business value. His main role as an ML Architect is to assist organizations in developing and maintaining machine learning pipelines by implementing MLOps principles, techniques, and tooling. He is well-versed in Feature Stores and has conducted internal training for Data Engineers, Data Scientists, and ML Engineers.

Richmond Alake

And when the world needed it most
He returned to talk about Agent Memory.

Day 74/100 of Agent Memory 🧠

Okay, I took a not so tiny break
But judging by the last few weeks… everything exploded)

While I was away, the memory discourse went from niche → mainstream almost overnight. In just the past week:
👉🏾 OpenAI improved ChatGPT’s cross-session memory
👉🏾 GitHub announced Copilot Memory in public preview
👉🏾 LlamaIndex frames “files as context substrates” for agents.
👉🏾 LangChain dedicated entire blogs and posts to memory patterns
👉🏾 Multiple startups are attempting to solve memory for Agents
👉🏾 And research papers are now using the phrase “Memory Units” without irony

This is what signal looks like.

For most of 2025, a lot of people treated Agent Memory like an optional add-on — something you sprinkle on top of prompt engineering or RAG. 

But the last 30–60 days have been the first real moment where the ecosystem collectively acknowledged that Memory is becoming a first-class primitive in the Agent Stack.

So as we approach the final quarter of this series, I’m going to keep dialing up the practicality:
✓ What is Agent Memory actually for?
✓ When should you build vs. adopt memory infra?
✓ How to reason about memory types (episodic, semantic, procedural, entity)
✓ How to design Memory Cores & memory lifecycles
✓ How production agents forget, consolidate, and retrieve
✓ And — most importantly — how to make agents less dumb over time

If you’ve been following since Day 1, the jump in ecosystem maturity is honestly encouraging(nothing beats validation from the AI ecosystem itself). 

If you're just joining, you’re entering at exactly the right moment.

Onwards to Day 75.

PS...I am going to tackle the following..so brace yourselves
1. Filesystem vs Database for Agent Memory (seriously though do I have to do this)
2. Why "One Memory Core for AI Agents" is how you should be thinking of your AI Infra
3. Build vs Buy when it comes to Agent Memory Solution

Let me know if there's any other topics or debates I should touch on.

#100DaysOfAgentMemory #MemoryEngineering #AgenticSystems #LLMEngineering #AIDev #ContextEngineering #AgentStack

The AI Stack Engineer | AI Strategist and Educator

I explain AI without putting you to sleep | AI Developer Advocate @ Oracle

Joined Oracle as an AI Developer Advocate.

Building demos. Writing tutorials. Making AI less confusing.

More soon.

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The Battle

Christina Stathopoulos, MSc

Richmond Alake

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taplio

The Battle

Christina Stathopoulos, MSc

Richmond Alake

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Christina Stathopoulos, MSc's LinkedIn Performance

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