Meetups
The Cloud-Edge AI Continuum
While deep ML models have been designed and operated mostly in the cloud, where there is enough computation power for their needs, we are starting to see a proliferation of ML models at the edge, on lower power devices. Increasing privacy awareness and latency are driving this trend of consuming data closer to its source.
In this talk, Valentin will focus on hybrid inference through splitting the model computations between the edge and the cloud. We ensure user data privacy by running the early computations of the model with raw data only on the edge. We will explore solutions for model inference but also training between the edge and cloud.
On March 15th, we're gathering for an introductory discussion to automatic differentiation where Bogdan will be talking about what automatic differentiation is, provide some examples and implememntation details.
Machine learning has become an indispensable part of modern society and continues to have a significant societal, economic and scientific impact.
First steps in AI, 2022 edition
On June 24th, we'll be hosting the third edition of First steps in AI, an event for all AI passionates that would like to study or continue studying artificial intelligence in one of the available academic programs from Iași.
For this event, our guests from Faculty of Computer Science, Mathematics, Automatic Control and Computer Engineering and Faculty of Electronics, Telecommunications and Information Technology will present the academic programs and courses that cover specific #AI topics in the upcoming academic year.
5 years anniversary
On June 14th we'll celebrate 5 years since our first meetup, back in 2017.
Join us at Acaju Cafe between 18:00 - 20:00 for a drink and some great conversations, along with community members and friends.
John is an international technology executive with over 35 years of experience in data and advanced analytics fields and has published two best-selling books on analytics and analytics teams, and has a 3rd book on the way.
John was an Executive Partner at Gartner, where he was management consultant to market leading companies in the areas of digital transformation, data monetization and advanced analytics. Before Gartner, he was responsible for the advanced analytics business unit of the Dell Software Group.
Scientific Machine Learning
Scientific Machine Learning (SciML) represents a blend of scientific computing and machine learning methodologies.
Traditionally, scientific computing relies on mechanistic modeling (ie., differential equations), with a focus on domain models based on physical laws and scientific knowledge. However, while mechanistic models of lots of scientific phenomena are routinely available, our computational capabilities are unable to keep up with the increasingly demanding requirements of realistic simulation.
In December, we continue AI Global Festival series with our second meetup on predicting building temperature using artificial intelligence.
Alexandru Lungu, Senior Software Engineer at E.ON Software Development will share a practical use-case on applying AI for predicting building inside temperature, optimize power comsumption and make life more sustainable.
AI is not just a technology but an enabler for business value creation. Hence, AI is increasingly important as a topic for business leaders and professionals.
For November, Xiaopeng Li, AI Business Lead at Microsoft and Oslo AI co-founder will share insights about the fundamentals of AI technology as well as the responsible approach for developing and applying AI solutions.
First steps in AI, 2021 edition
On 16th of June, we'll be hosting the second edition of First steps in AI, an event for all AI passionates that would like to study or continue studying artificial intelligence in one of the available academic programs from Iași.
For this event, similar with the 2019 edition, our guests from Faculty of Computer Science, Mathematics, Automatic Control and Computer Engineering and Faculty of Electronics, Telecommunications and Information Technology will present the academic programs and courses that cover specific #AI topics in the upcoming academic year.
In May, we'll explore how to create Named Entity Recognition Systems. We're starting with identifying specific classes of entities from a given text-based dataset and learn how to install and use the necessary Python tools. In this month's talk we will show how to create, in a step-by-step manner, the components needed for creating custom NER systems.
Andrei, Data Scientist at SenseTask, will share how to do all this by leveraging Python's powerful set of open-source NLP libraries.
April is about tech and healthcare, as we'll be sharing insights into patients data, medical image processing and what are the best metrics and specific biases for machine learning models in medicine. More, we'll go through some relevant particularities of the domain knowledge in medical AI and the approach for developing AI projects using public medical datasets.
Charles Delingpole, CEO of ComplyAdvantage will join us for a fireside chat on artificial intelligence and how can machine learning help wiping out financial crime.
Meet Louison Dumont, Founder of Bitproof which developed Harmony, a cross platform voice agent builder. Using proprietary NLU and data augmentation methods, Harmony allows its users to easily build rich voice-enabled interfaces.
In January, we'll be entering into IBM world, learning how machine learning can obtain and provide valuable insights on customer behavior and dive into a brief look in the future and the usage of quantum computing when solving maching learning algorithms. More, Cristina, and Mihai, our speakers for this meetup will showcase IBM Auto AI and IBM Watson Studio.