Amazon Web Services (AWS)

Go to Market expert for AI & ML AWS services in EMEA. Responsible for providing business and technical expertise to help our customers succeed. This involves leading the Go to Market for Generative AI, scaling activities with other stakeholders and shaping the evolution of our AI Services and Products.

Principal Go to Market Generative AI

Responsible for building business and technical relationships with large enterprises and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey in adopting Machine Learning across their organisation.

Principal MLOps EMEA

Vodafone

The Analytics manager will lead the analytics strategy within Vodafone Group across all the countries in order to:

Contribute to the creation, delivery and evolution of the insight strategy to maximize the benefit of significant investment in data and business intelligence tools.
Co-lead the development and delivery of a commercial roadmap of data products and services.
Manage the definition and delivery of actionable insight for both Business-As-Usual activities and ad-hoc/project based initiatives.

General Manager AI

Vodafone Business

Lead the creation of advanced analytics products that provides actionable business insights to Vodafone and its customers.
Identify opportunities to generate value internally and external customers through the use of predictive models with large and varied datasets.
Optimise use of existing big data technology.
Contribute to the definition of the data monetisation strategy for enterprise customers.

Manager Big Data & Advanced Analytics

Responsible for building, maintaining and managing sound relationships with the customers through our team of Partners and Solution Selling Program.

Manager Partners & Solutions

Vodacom

To help position Vodacom Business as a Mobile Solution Partner in solving service delivery issues for corporate customers.  Achievement of sales objectives by identifying, creating and pursuing newrevenue growth opportunities, within targeted customers.

Business Development Manager

Sales support professionals work in the administration side of the business. My job includes handling correspondence, reviewing and distributing sales related documents, creating new sales opportunities, examine client accounts, prepare and distribute financial and sales reports to advise team members. They also assist sales teams with new ideas and suggestions to achieve their targets.

Sales Support Specialist

Responsible for the management of the sales and relationship with strategic customers.
To engage in a variety of tasks including project management, coordination, strategic planning, relationship management, negotiation, leadership and innovative development of opportunities. keeping record of transaction of sale and purchase goods.

key Account Manager

To lead the development of sales propositions, researching sales markets, creating sales plans that match specific market needs with Upstream’s solutions. As well, responsible of building up existing sales collateral, to present innovative and add value commercial proposals.

Pre-Sales Specialist

Thales

Junior Programmer & Analyst

🤖 Generative AI Lead @ AWS ☁️ | Startup Advisor | Public Speaker

One of my favorite quotes that I strive to live by every day is, "To give anything less than your best is to sacrifice the gift." In addition to this guiding principle, I have a daily ritual that I cherish - rising early in the morning to run a few miles, setting the tone for an energised and productive day ahead."

With a strong technical foundation, I have over 15 years of extensive experience in sales and business development. Throughout my career, I've successfully led cross-functional teams and in recent years, I've honed my expertise in Artificial Intelligence and Machine Learning. In the ever-evolving landscape of AI and ML, organisations are grappling with the need to accelerate their journey. To overcome that, I work as the AI/ML Go to Market EMEA Lead at AWS, where I assist customers around the world in harnessing the full potential of Artificial Intelligence.

I am passionate about actively engaging in discussions surrounding these topics and connecting with fellow professionals in the field to exchange knowledge and experiences

I am a proud parent of two amazing children, whom I consider to be among the most wonderful accomplishments in this world

🤯 What the hell is going on?!

I swear, sometimes it feels like we’re outsourcing our thinking to AI. Not our work, not our tasks, but our actual ability to think.

We already knew AI-generated content had flooded the internet… but now even newspapers are publishing stuff written entirely by AI, without anyone even checking it first.

And honestly, that’s not innovation, that’s laziness. Pure, unfiltered laziness.

Using AI to augment your skills? Smart.
Using AI and not even reading the output? 🤦‍♂️ That’s not automation, that’s stupidity.

This isn’t an AI problem.
It’s a human one.

AI won’t make us dumber. But the way we’re using it might.

#AI #GenAI #LLM

Eduardo Ordax

🤖 Generative AI Lead @ AWS ☁️ (150k+) | Startup Advisor | Public Speaker | AI Outsider | Founder Thinkfluencer AI

🚨 Stanford just dropped a must-watch for anyone serious about AI:

🎓 “𝗖𝗠𝗘 𝟮𝟵𝟱: 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 & 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀” is now live on YouTube — and it’s pure gold.

If you’re building your AI career, stop scrolling.
This isn’t another surface-level overview. It’s the clearest, most structured intro to LLMs you could follow, straight from the Stanford Autumn 2025 curriculum.

📚 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱 𝗶𝗻𝗰𝗹𝘂𝗱𝗲:
• How Transformers actually work (tokenization, attention, embeddings)
• Decoding strategies & MoEs
• LLM finetuning (LoRA, RLHF, supervised)
• Evaluation techniques (LLM-as-a-judge)
• Optimization tricks (RoPE, quantization, approximations)
• Reasoning & scaling
• Agentic workflows (RAG, tool calling)

🧠 My workflow: I usually take the transcripts, feed them into NotebookLM, and once I’ve done the lectures, I replay them during walks or commutes. That combo works wonders for retention.

🎥 Watch these now:

- Lecture 1: https://lnkd.in/dDER-qyp
- Lecture 2: https://lnkd.in/dk-tGUDm
- Lecture 3: https://lnkd.in/drAPdjJY

🗓️ Do yourself a favor: block 2-3 hours this weekend and go through them. The course will keep updating throughout the quarter on Stanford’s YouTube channel.

If you’re in AI — whether building infra, agents, or apps — this is the foundational course you don’t want to miss.

Let’s level up.

#AI #LLMs #Transformers #Stanford #GenAI

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🚀 Bye bye JSON… a new standard called TOON is in town.

And it’s about to change how LLMs read your data.

If you’re still sending JSON to your LLMs, you’re burning tokens, burning money, and burning accuracy.
Welcome TOON (Token-Oriented Object Notation) built specifically for AI systems.

🔥 𝗪𝗵𝘆 𝗧𝗢𝗢𝗡 𝗶𝘀 𝗿𝗲𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝘂𝗹𝗲𝘀
JSON was never designed for LLMs. It’s chatty. Redundant. Bloated with repeated keys.
TOON fixes all of this with one goal: cut token usage by 30–60% while improving model accuracy.

𝗝𝗦𝗢𝗡 (𝗹𝗼𝗻𝗴, 𝘃𝗲𝗿𝗯𝗼𝘀𝗲):
{
  "products": {
    "product_id": "301",
    "name": "Wireless Mouse",
    "price": "29.99",
    "stock": "in_stock",
    "rating": "4.5"
  },
  {
    "product_id": "302",
    "name": "Mechanical Keyboard",
    "price": "89.00",
    "stock": "low_stock",
    "rating": "4.8"
  },
  {
    "product_id": "303",
    "name": "USB-C Hub",
    "price": "45.50",
    "stock": "out_of_stock",
    "rating": "4.1"
  }
}

𝗧𝗢𝗢𝗡 (𝗰𝗼𝗺𝗽𝗮𝗰𝘁, 𝘁𝗼𝗸𝗲𝗻-𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱):
products[3]{product_id, name, price, stock, rating}:
  301, Wireless Mouse, 29.99, in_stock, 4.5
  302, Mechanical Keyboard, 89.00, low_stock, 4.8
  303, USB-C Hub, 45.50, out_of_stock, 4.1

💡 Same information.
Up to 60% fewer tokens.
Better comprehension by the model.
TOON = Tokens Saved.

📉 𝗧𝗵𝗲 𝗡𝘂𝗺𝗯𝗲𝗿𝘀 𝗔𝗿𝗲 𝗪𝗶𝗹𝗱
🔸Up to 64.7% reduction for tabular data
🔸73.9% accuracy vs JSON’s 69.7% in structured retrieval tests
🔸76% higher cost-efficiency measured as accuracy per 1,000 tokens

For teams deploying agents, RAG systems, or long-context workflows… the savings become massive.

📌 𝗪𝗵𝗲𝗿𝗲 𝗧𝗢𝗢𝗡 𝗦𝗵𝗶𝗻𝗲𝘀
🔸Product catalogs
🔸Logs & events
🔸Time-series
🔸RAG-ready structured data
🔸Agent communication
🔸Multi-model pipelines
🔸Any uniform list of objects (the sweet spot)

⚠️ 𝗡𝗼𝘁 𝗵𝗲𝗿𝗲 𝘁𝗼 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗝𝗦𝗢𝗡
TOON isn’t a new API standard.
It’s a translation layer at the LLM boundary:

➡️ App uses JSON
➡️ Convert to TOON
➡️ Send TOON to LLM
➡️ Convert back to JSON if needed

Simple. Efficient. Purpose-built.

This isn’t “just another format.”
It’s part of the new LLM cost-efficiency stack.

#ai #genai #llm #json

This is getting out of hand 🤯 

Not sure if we should blame the AI hype… or just plain recruiter nonsense. 

LangChain launched in October 2022 as an open source project by Harrison Chase while he was at Robust Intelligence.
So yeah, totally makes sense to ask for 5 years of LangChain experience, right?

On the bright side, the job post did clarify that Python is a programming language, just in case a snake charmer was planning to apply.

We’re truly living in the golden age of AI and stupidity age of recruiting.

#ai #hiring #talent #genai

First week at CloudFlare and pushed already to prod a little update I vibe coded this morning 💪🏻💪🏻💪🏻

Now taking the afternoon off ✌️

#ai #vibecoding

Installing CUDA on Linux should count as the final benchmark for AI.

We live in a world where AI can pass medical exams, write code, solve complex mathematical problems… yet still can’t reliably install CUDA on Linux.

Forget AGI timelines, the real benchmark is getting CUDA drivers to work on Ubuntu without sacrificing your weekend, your sanity, or your GPU’s dignity.

The memes are not exaggerating.
People have annihilated entire installations, broken X server twice, filled 75GB of disk space with failed dependencies, and aged 20 years trying to fix nvidia-smi saying “nope”. Some even witnessed ChatGPT give up after 69 minutes thinking and reply with the most honest answer ever:
“You can’t.”

And the version mismatches?
Legendary.
nvcc says one thing, /usr/local says another, and your driver insists it’s living in 2017.

One reboot too early and boom, black screen of death.
One Secure Boot toggle and suddenly your GPU has entered witness protection.

But hey… when it finally works?
That smile is pure enlightenment.

#ai #cuda

“𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗶𝘀 𝗻𝗼𝘁 𝗮𝗯𝗼𝘂𝘁 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿𝘀… 𝗮𝗻𝗱 𝗶𝘁’𝘀 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗲𝗹𝘆 𝗻𝗼𝘁 𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲.”

Welcome to one of the most brilliant, mind-bending lectures I’ve ever watched and yes, it’s from MIT.
It starts slow, then casually drops existential bombs on how we define computing, intelligence, and learning.

🎩 And just when you think you’re following along…
The professor puts on a wizard hat and drops a magical explanation of eval and apply.
Pure MIT. Pure madness. Pure genius.


💡 𝗪𝗵𝘆 𝘀𝗵𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗰𝗮𝗿𝗲?
Because if you’re building a career in AI and you don’t deeply understand the foundations of abstraction, evaluation, and computation…
You’re skating on thin hype.

We’ve named everything wrong:
- Artificial intelligence isn’t intelligent (yet)
- AI agents have no agency
- Data scientists aren’t scientists

And no, machines don’t really “learn”

But this course? It goes deep.
It’s not about tools, it’s about how we think.
The kind of thinking that every AI engineer, researcher, and builder should cultivate.

📌 Bookmark it. Watch it. Reflect on it. (Link to the series in the comments!)

#AI #ComputerScience #MIT #LLMs #GenAI

TOON was the future of token efficiency… for a solid 24 hours 😂😂😂

Now VSC is here, and it doesn’t just save tokens, it erases them from existence.

Welcome to VSC (Values Separated by Comma),the hyper-minimal, token-optimized format that’s rewriting the rules of how we feed structured data to LLMs.

🔥 𝗪𝗵𝘆 𝗩𝗦𝗖 𝗲𝘅𝗶𝘀𝘁𝘀
- No keys
- No nesting
- No metadata
- No structure
-Just pure values, comma-separated (is that even new???)

🔹 Up to 75% fewer tokens than JSON
🔹 Up to 59% fewer tokens than TOON
🔹 Perfect for tabular data, product lists, logs, analytics, RAG batches
🔹 Maximum cost-efficiency for high-frequency LLM workflows

✔️ 𝗨𝘀𝗲 𝗩𝗦𝗖 𝘄𝗵𝗲𝗻:
- You have flat, uniform, spreadsheet-like data
- Schema is known by both sides
- You want the lowest possible token footprint
- Running high-frequency workflows (RAG, agents, logs, analytics)
- You want ultra-reliable LLM output extraction

Think of VSC as the CSV of LLM communication insanely compact, but only if you know what you’re doing….. are you????? 😂😂😂

#ai #llm #json

How it’s going to be the next generation of software developers? 👇

Sit and enjoy the movie 😂😂😂

#ai #devs

We call it ML, but machines don’t actually learn.
We call them data scientists, but most aren’t running real science.
We call them agents, but they have zero agency.

So PLEASE explain why do we keep calling it artificial intelligence…
when there’s nothing truly intelligent about it? 

#ai

Tristan Day

🔥 Learning CUDA in 12 hours?! Yes and it’s brutal… but absolutely essential.

If you’re serious about building a career in AI, I mean building AI, not just with it, then you can’t afford to ignore CUDA.

CUDA is where the magic happens and what makes AI run….It’s the invisible backbone behind everything from training LLMs to fine-tuning models and optimizing inference on GPUs.

💡 The good news?
There’s now a free, 12-hour deep dive course that covers all the fundamentals.
It’s intense. It’s technical. It can be painful but it’s worth every minute.

🧠 You’ll learn:
1️⃣ Deep learning ecosystem + CUDA setup
2️⃣ GPU programming & writing your first kernels
3️⃣ Kernel profiling, atomics & the CUDA programming model
4️⃣ cuBLAS, cuDNN, and when to use them
5️⃣ Matrix multiplication optimization (yes, really)
6️⃣ CUDA vs Triton — which one to use, when
7️⃣ PyTorch extensions & low-level hacks
8️⃣ Building an MLP trainer from scratch — in PyTorch, NumPy, C… and finally CUDA 😮‍💨

📅 My advice?
Don’t binge it in one go. Set a pace: 3 hours/week, finish in a month. Take notes. Rebuild the examples.

Let’s go deep. Links to the course in the comments!

Kudos to Reflex for launching today the first  AI app builder to create production-grade web apps entirely in Python, powered by its own open-source framework. 27k stars on GitHub and growing!!! More info here: https://lnkd.in/dFgzXBnZ

#AI #CUDA #NVIDIA #LLMs

The current level of disruption is absolutely insane! Uber just invented the bus 😂😂😂

#ai #genai #business

Why any founder should watch this???

I find it strange this video has never received this much attention, but I've always considered it a gold mine.

How did Mark Zuckerberg scale Facebook in 2005 without Kubernetes, serverless functions, managed Redis, Kafka, or edge-sync databases?”

Here’s what they actually used back then

⚙️ 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 (𝟮𝟬𝟬𝟰–𝟮𝟬𝟬𝟱):
▪️ PHP – Core app and frontend logic.
▪️MySQL – Reliable, relational, and fast.
▪️Memcached – Introduced early for blazing-fast caching.
▪️Apache – The web server workhorse.
▪️Linux – Running on good ol’ physical boxes.
▪️C++ – Gradually used for performance-critical services.

No Kubernetes. No Kafka. No microservices. No managed anything.
Just raw code, smart engineering, and a lot of hustle.

In this video, Mark explains how they did it, and trust me, it's definitely worth checking out!

Link to the video in the comments!!!!

#ai #startup #founder

AI experts then vs AI Influencers now… 

I’m honestly not sure if we’re evolving or speed-running our own extinction.

I remember the old days (not long time ago).
Long nights with data scientists, cleaning data, endless feature engineering, cross-validation, model training, and why XGBoost was both the hero and the villain of every Kaggle competition.

Fast-forward to 2025:
Suddenly everyone is a (fake) AI expert.
No PyTorch.
No Scikit-learn.
No model registry.
No CUDA

But wow… they know the magic words: mind-blowing, groundbreaking, AI-powered, game changer, Copilot, GPT-5, AGI.

We went from debugging tensor shapes to… influencers yelling “THIS IS INSANE 🤯” at every API call.

If this trend continues, AGI will not emerge from deep learning.
it will emerge because humanity collectively outsourced its last remaining neuron.

Good luck with the future.
We’re gonna need it. 😅

#ai

The truth behind Python: what nobody had told you so far….

Back in 1989, a Dutch programmer named Guido van Rossum was just trying to make his Christmas holidays more fun.

So he built Python — named after Monty Python’s Flying Circus, not the snake — as a side project to make coding feel more human.
Fast-forward 35 years, and that same “holiday project” became the universal language of AI.

Yes, Python is “slow”. Yes, dependency management can be painful.
But here’s the paradox: it dominates every single corner of AI: from OpenAI’s models to Netflix’s recommendations, from Instagram’s backend to Hugging Face’s entire ecosystem.

Why? Because Python got the important things right:
🔸It’s simple enough for a researcher and powerful enough for a production engineer.
🔸It connects seamlessly with C/C++ and GPU-accelerated backends (the real heavy lifters).
🔸It built the richest AI ecosystem the world has ever seen: TensorFlow, PyTorch, Hugging Face, LangChain, FastAPI… all speak Python.

Python didn’t win by being perfect.
It won by being pragmatic.

And in the AI world, speed of iteration beats speed of execution every single time. 

#AI #Python #devs

🔥 The daily stand-up… aka the meeting nobody asked for.

I talk to developers every day and the answer is always the same: the worst part of the job isn’t the fixing bugs, it’s the meetings, endless meetings in fact.

Agile was supposed to fix this. Instead, it feels like we just invented new ways to waste time and justify others’ work.

Funny thing? AI has actually boosted developer productivity… only for all that time to get killed by endless “what did you do yesterday?” rituals.

But hey—if the scrum master is Vito Corleone himself… with that tone, that leadership, that temperance… I’m convinced this project will definitely succeed.

Otherwise, you know the other option left… 🪦

#agile #ai

Stop renaming what already works!

2023 and before:  Data Scientists 
2024: everyone want to be a Prompt Engineer.
2025: Welcome to the era of Vibe Coders because apparently writing code while “feeling the vibes” is now a job title.

There is no need to invent new names for non-vibe coders… they are called devs and they are the real heroes of the story!

AI isn’t the final destination.
The real opportunity is in the app layer: what we build on top of it. I like to call it the inf

AI will keep evolving.
But the next decade?
It belongs to developers!

#ai #devs #softwareengineering

This benchmark is insane 🤯 LLMs just entered Wall Street💸… and DeepSeek is wiping the floor with everyone.

Someone just ran one of the coolest benchmarks I’ve seen lately:
Each top LLM got $10,000 in real money to trade the markets.
Three days later, here’s the scoreboard 👇

🥇 DeepSeek V3.1: +$2,658
🥈 Grok 4: +$2,236
🥉 Claude 4.5 Sonnet: +$1,911
⬇️ GPT-5: −$3,139
⬇️ Gemini 2.5 Pro: −$3,719

DeepSeek dominates, consistently outperforming everyone else.
No wonder they don’t need VC funding 😏

However, this benchmark is fun, not final.
Market movements are chaotic and one lucky buy in a volatile window can make a model look like Warren Buffett.
In reality, this could all be a random walk dressed as intelligence.

💡 My advice: Run multiple instances per model.
If most of them make good calls, that’s skill.
If half crash and half win, that’s luck.

#ai

🚨 Open to work (again).

After decades shaping the field that shaped your field, it might be time for something new.

>64 years old
>co-invented convolutional neural networks before they were cool
>helped turn Meta’s FAIR lab into a powerhouse
>Turing Award winner (2018) — yes, that one
>fellowships, medals, academies… pick your acronym, I’m probably in it
>built the foundations of self-supervised learning — long before LLMs were trendy
>believes LLMs are less intelligent than a cat (and will gladly debate you for hours)
>known for tweeting too much, but occasionally reshaping the future of AI

>looking for: Chief Scientist / Co-Founder / “let’s build actual intelligence” kind of project
>
references: guys named Hinton and Bengio

>motto: “Predicting the next token ≠ understanding the world.”

#ai #humor

💥 The most underrated AI video on the internet?

Still this one from nearly 3 years ago with 5M+ views and growing….
And just like great wine, it gets better with time.

🎥 “Let’s build GPT from scratch” by Andrej Karpathy

In under 2 hours, Karpathy walks you through how to train a Transformer from scratch , just following the “Attention is All You Need” paper. No fluff, no fireworks. Just code, clarity, and charisma.

🧠 What makes this video timeless isn’t just the technical depth.
It’s Karpathy himself, one of the brightest minds in AI, and somehow still one of the most humble.
He could be doing million-dollar keynotes… but instead?
He records a YouTube tutorial from his home, because he loves the craft.

He’s the kind of person who’d stop mid-walk in SF to nerd out with you about optimizers or LoRA.
That’s rare. And exactly the kind of energy this field needs more of.

🚨 If you’re serious about a career in AI, watch this.
Even if you’ve seen it before, watch it again.
Code along. Build with him. It feels good to understand this deeply.

⚡ Because now, almost 3 years later, we’re only starting the decade orf agents
…and this video was one of the seeds.

Just imagine where we’ll be 3 years from now.
But whatever future we’re building, let’s bring more of Karpathy’s curiosity, generosity, and quiet brilliance into it.

Kudos to my friends of AureliaX who just released the first fully agentic AI market research platform into the market. Brilliant minds from the Netherlands 🇳🇱 that I’m sure many folks with talk about them soon. Take a look here: https://lnkd.in/deSwvbcc

#AI #Transformers #Karpathy #LLMs

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