Orchestrate all the Things
George Anadiotis
Connecting the dots with George Anadiotis: Analyst, Consultant, Engineer, Founder, Host, Researcher, and Writer.
Stories about Tech, Data, AI and Media, and how they flow into each other shaping our lives.
I’ve engaged from the likes of Gary Marcus and Andrew Ng to emerging thinkers and innovators across multiple domains.
My stories have been featured on ZDNet and VentureBeat, and are syndicated across DZone, Hackernoon, Medium and Substack.
Some might call this futurism; let’s just say it’s connecting the dots
Many conversations have a technical focus. Most also examine business perspectives and use cases, while others are socio-technical.
Some are analyses on emerging themes – picking them up early, featuring expert comment, or offering alternative takes.
Others cover breaking news, typically also featuring the people behind them plus some analysis. There are some book reviews as well.
I focus on the connection between data, analytics, data science, graphs, machine learning and AI and their impact on society and business.
I have been covering topics related to:
AI and Machine LearningData, Analytics and Data ScienceKnowledge Graphs, Graph Databases, Graph AI & Data ScienceInnovation, and a wide array of technologies such as Blockchain, Cloud, Observability, IoT, Open Data and Open Source, Social Media and Software Engineering.
For inquiries, please use https://linkeddataorchestration.com/contact/
Stories about Tech, Data, AI and Media, and how they flow into each other shaping our lives.
I’ve engaged from the likes of Gary Marcus and Andrew Ng to emerging thinkers and innovators across multiple domains.
My stories have been featured on ZDNet and VentureBeat, and are syndicated across DZone, Hackernoon, Medium and Substack.
Some might call this futurism; let’s just say it’s connecting the dots
Many conversations have a technical focus. Most also examine business perspectives and use cases, while others are socio-technical.
Some are analyses on emerging themes – picking them up early, featuring expert comment, or offering alternative takes.
Others cover breaking news, typically also featuring the people behind them plus some analysis. There are some book reviews as well.
I focus on the connection between data, analytics, data science, graphs, machine learning and AI and their impact on society and business.
I have been covering topics related to:
AI and Machine LearningData, Analytics and Data ScienceKnowledge Graphs, Graph Databases, Graph AI & Data ScienceInnovation, and a wide array of technologies such as Blockchain, Cloud, Observability, IoT, Open Data and Open Source, Social Media and Software Engineering.
For inquiries, please use https://linkeddataorchestration.com/contact/
Episodes
Mentioned books
Oct 14, 2021 • 42min
The State of AI Report, 2021. Featuring AI Investors Nathan Benaich and Ian Hogarth
It's this time of year again: reports on the state of AI for 2021 are out.
In what is becoming a valued yearly tradition, we caught up with AI investors and authors of the State of AI report, Nathan Benaich and Ian Hogarth, to discuss the 2021 release.
Some of the topics we covered are lessons learned from operationalizing AI and MLOps, new concepts and datasets, language models, AI ethics, and AI-powered biotech and pharma.
Article published on ZDNet
Sep 28, 2021 • 22min
Open-source backend as a service Appwrite gets $10M seed funding to commercialize traction. Featuring CEO / Founder Eldad Fux
Appwrite, an open source platform that offers a slew of features to developers, aims to capitalize on its grass-roots popularity.
Article published on ZDNet
Sep 22, 2021 • 28min
An AI-powered revenue operating system for aviation and beyond: FLYR Labs Lands $150 Million in Series C Funding. Featuring CEO / Founder Alex Mans
A multi-trillion dollar business in crisis, upending incumbents, unfettered ambition, and pragmatic deep learning. FLYR's story has it all.
Article published on ZDNet
Sep 21, 2021 • 55min
Machine learning at the edge: A hardware and software ecosystem. Featuring Alif Semiconductors Sr. Marketing Manager Henrik Flodell, Arm Director of Ecosystem and Developer Relations Machine Learning Philip Lewer, Neuton CTO Blair Newman
Henrik Flodell, Philip Lewer, and Blair Newman discuss the significance of hardware and software cooperation for deploying machine learning applications at the edge. They explore Neuton's architecture, optimizing power draw for cellular enabled devices, and future plans for growth in the tiny ML and AI on the edge space.
Sep 10, 2021 • 58min
DeepMind wants to reconcile Deep Learning and classical computer science algorithms with Neural Algorithmic Reasoning. Featuring DeepMind's Petar Veličković and Charles Blundell, MILA's Andreea Deac
Will Deep Learning really be able to do everything? We don't really know.
But if it's going to, it will have to assimilate how classical computer science algorithms work. This is what DeepMind is working on, and its success is important to the eventual uptake of neural networks in wider commercial applications.
This work goes by the name of Neural Algorithmic Reasoning. Join us as we discuss roots and first principles, the defining characteristics, similarities and differences of algorithms and Deep Learning models with the people who came up with this.
We also cover the details of how Neural Algorithmic Reasoning works, as well as future directions and applications in areas such as path finding for Google Maps
Could this be the one algorithm to rule them all?
Article published on VentureBeat.
Image: Getty
Sep 2, 2021 • 38min
The State of MLOps in 2021. Featuring New Relic Lead Researcher Ori Cohen and Monte Carlo Co-Founder Lior Gavish
MLOps is the art and science of bringing machine learning to production, and it means many things to many people. The State of MLOps is an effort to define and monitor this market
Article published on ZDNet
Aug 17, 2021 • 47min
Apollo GraphQL announces $130 Million Series D Funding, wants to define its own category. Featuring CEO & Founder Geoff Schmidt
GraphQL is a specification that came at just the right time to address an age-old issue in software engineering: service integration. Apollo's implementation is seeing lots of traction, and it just got more gas in the tank for its grand vision that goes well beyond integration.
Article published on ZDNet
Jul 19, 2021 • 31min
MLGUI: Building user interfaces for machine learning applications. Featuring KPMG Germany Senior Data Engineer Philip Vollet
Machine learning is eating the world, and spilling over to established disciplines in software, too. After MLOps, is the world ready to welcome MLGUI?
Philip Vollet is somewhat of a celebrity, all things considered. Miley Cyrus or Lebron James he is not, at least not yet, but if data science lives up to the hype, who knows.
As the senior data engineer with KPMG Germany, Vollet leads a small team of machine learning and data engineers building the integration layer for internal company data, with access standardization for internal and external stakeholders. Outside of KPMG, Vollet has built a tool chain to find, process, and share content on data science, machine learning, natural language processing, and open source using exactly those technologies, which makes for a case of meta, if nothing else.
There is a flood of social media influencers sharing perspectives on data science and machine learning. While most influencers direct their attention solely toward issues of model building and infrastructure scaling, Vollet also looks at the user view, or frameworks for building user interfaces for applications utilizing machine learning. We were intrigued to discuss with him how building these user interfaces is necessary to unlock AI's true potential.
Article published on VentureBeat.
Photo by Kelly Sikkema on Unsplash
Jul 7, 2021 • 37min
Open source growth and venture capital investment: data, databases, challenges and opportunities. Featuring Runa Capital Principal Konstantin Vinogradov
Konstantin Vinogradov, a Principal at Runa Capital, shares insights on the evolving landscape of open source software and its commercialization. He discusses how investors are now recognizing the potential of open source companies, shifting from skepticism to acceptance. The conversation delves into metrics for evaluating open source projects and introduces a new growth index based on GitHub data. Konstantin also explores successful ventures like Athens Research in the competitive note-taking market and the diverse dynamics of funding in open source.
Jun 22, 2021 • 53min
More than words: Shedding light on the data terminology mess. Featuring Soda Founders Maarten Masschelein and Tom Baeyens
It's a data terminology mess out there. Let's try and untangle it, because there's more to words than lingo.
Hopefully technology investment decisions in your organization are made based on more than hype. But as technology is evolving faster than ever, it's hard to keep up with all the terminology that describes it. Some people see terminology as an obfuscation layer meant to glorify the ones who come up with it, hype products, and make people who throw terms around appear smart.
There may be some truth in this, but that does not mean terminology is useless. Terminology is there to address a real need, which is to describe emerging concepts in a fast moving domain. Ideally, a shared vocabulary should facilitate understanding of different concepts, market segments, and products.
Case in point - data and metadata management. Have you heard the terms data management, data observability, data fabric, data mesh, DataOps, MLOps and AIOps before? Do you know what each of them means, exactly, and how they are all related? Here's your chance to find out, getting definitions right from the source - seasoned experts working in the field.
Article published on ZDNet
