Agenda

With little exception, present AI technology is totally dependent on previous human thought, thought either in the form of human-written algorithms or in the form of human-generated sample solutions. True intelligence is the ability to pursue general goals in changing environments. I will discuss the stumbling blocks that stand in the way of achieving that in silico and how to remove them.

In this talk we present Prospex, the AI-driven sales lead generator. Prospex combines graph theory with reinforcement learning techniques to figure out what an ideal client’s DNA looks like for any given salesperson, working for any given company in any given industry. We will discuss how Prospex was born, how it can be used and take an overview into the Science behind this matchmaking engine.

AISoft Technology is developing innovative framework for building smart real-time monitoring and AI solutions for delivering seamless observability of big data systems, which in the end has a goal of reaching autonomous system operations and maintenance. The hart of observability in big data systems is a powerful autonomous…

The talk will recall the remaining challenges for autonomous driving on road. How AI and deep learning is considered in perception, motion planning, localization, mapping and driver monitoring? How complex is the scaling problem, from country to country? How much data is needed? Is it possible to guarantee safety of AI decisions? The talk will also describe the AI challenges at extremely high-speed and some insight of our work will be presented.

All companies who are looking into the future are developing AI as part of their business. How can the biggest Croatian IT company be any different?! Trough this talk they will share their vision.

When it comes to the support experience, customers seek familiar, informal, and, most important, immediate forms of contact. That’s why, for brands seeking to interact directly with consumers, real-time communication is a no-brainer. Machine learning and chatbots can extend your customer service by helping customers resolve common issues, using back end services such as CRM and ERP to provide relevant information and to…

AI, or more precisely machine learning, brings many benefits to “real industries“ – from wood processing factories to food and beverages, all of them are built out of common building blocks. By adding even basic ML capabilities to them such as anomaly detection or pattern matching, measurable increase in efficiency and productivity can be achieved. If you add edge/fog computing to the mix with DNN ran directly side-by-side…

AI is now a global business. Competition is fierce, and the field is constantly evolving. One has to keep track of all new approaches and techniques while keeping an eye on new fields of applications and business opportunities. We will show how we deal with staying on the cutting edge of research in AI while solving real-world industry problems…

An onsite video camera captures the scene, and a device inside the station running Microsoft Azure IoT Edge can now use artificial intelligence tools to pick out that behavior — out of all the cars coming and going, drivers cleaning windshields, customers buying snacks — as a potential safety risk. It’s a first line of defense on the “intelligent edge,” where data is…

Value creation in the software industry has intriguingly shifted towards reusing the existing components and services on a high level, focusing on solving problems for existing or emerging markets. This has also affected the field of AI. As the result of a quick adaptation, the AI technology and related services have become increasingly accessible – from machine learning frameworks, tons of application-specific libraries and SDKs, and cloud-based AI solutions, to data collection and…

If you’re building an AI company or building out AI expertise within your organization it might seem like there are lots of low hanging fruits, ready to be picked. Most of organizations or your potential clients use data and AI in a very limited way so it’s not hard to achieve early successes. But if you want to win in the long run, then you must be aware that some battles are not to be fought because they are already lost. This presentation is for those who play to win.

The presentation will provide a brief overview of existing regulatory framework and definition of AI with special emphasis on EU. The challenges and opportunities of shared and common global AI framework will be discussed.

Supervisory practices and scaling up of technological innovation in the financial sector

Financial services are becoming increasingly sophisticated and technology-enabled. Market participants and regulators may find it difficult to understand financial innovations and their implications in the regulatory framework. Without the appropriate environment, financial innovation may decelerate. Financial regulators have responded to such challenges by introducing innovative regulatory initiatives.

As research in AI shows, AI is increasingly used in education and learning environments. The impact of three areas – data, computation and education – will have far reaching consequences, raising fundamental questions about the nature of education – what is taught and equally importantly how it is taught.

In this talk, we will try to examine how AI may impact the curriculum design, the individualization of learning, and the…

There is no single country in the world that is not preparing itself for the age of new technologies and platforms. One of the most important ones is Artificial Intelligence – everyone expects that it will change the world, but also to drive new economic progress for the countries that want and invest into it. European Union is making sure that we are not behind and there are numerous initiatives and investments into the Artificial Intelligence. What about Croatia? What is Croatia…

Trough the presentation we will explore and illustrate a range of ethical issues with AI, from classical AI ethics, such as bias in training data and privacy issues around data sourcing and management, to the future of artificial general intelligence and the potential for artificial consciousness and sentient artificial beings.

If you already have a carrier in software development and you would like to switch to machine learning/artificial intelligence, this is a talk for you. I will talk about my personal journey into the field, starting from my own motivation to concrete steps I took to make the transition.

AI field is vast and possibilities are endless. AI is starting to feel like buzz word and everybody is racing to take position as AI company or organization that utilize an AI technology to drive future development. EU recently announced strong investments in the field and some 2,8 bn euros will be dedicated to AI projects in the next budget 2021-2027. This all represent a huge opportunity.
But is AI just the buzzword or we are approaching a next era of business and society? In what direction should organization place their effort and resources regarding AI technology? Should AI start-ups narrow fields in which they are developing products and services? What technology start-ups need to take into consideration when developing AI based projects? What are investors looking when they want to invest money into AI company?
Idea is to give few guidelines to people (and companies) thinking about investing their time and money into future of AI.