DSC Europe 2022
2022-11-14..2022-11-18
-- online --
| title | author | length |
|---|---|---|
| Aftermovie | 01m | |
-- no description -- | ||
| Do what you do best… | Casper Pedersen | 39m |
Claims a practical stack: deploy a full SAS Viya instance on Azure Marketplace in under an hour with JupyterHub, support for SAS/Python/R, and built-in model… | ||
| Predictive NPS (PNPS) | Martin Dimov | 33m |
Claims to predict NPS for every customer rather than the usual 10–15% survey response by producing 100% coverage scores from combined CRM billing usage… | ||
| Building a recommendation system for EPAM systems | Vladimir Ageev | 25m |
Enterprise video platform for thousands of employees uses a hybrid recommender: candidate generation with LightFM over a ~100,000-video corpus (≈300… | ||
| A story arc for responsible AI | Seth Dobrin | 22m |
Companies that prioritize responsible AI show better business outcomes even among AI leaders, and organizations that integrate risk mitigation report higher… | ||
| Empowering journalism-approaches to automatic text summarization | Milena Djordjevic | 22m |
Sees 70% of words go unread and claims ~28% of content drives understanding and attention averages 8 seconds, so TX Services gathers article–summary pairs… | ||
| Make some noise for AI in JavaScript! | Sead Delalic | 29m |
Client-side noise suppression implemented for Infobip WebRTC uses an RNNoise-based model retrained with mixed clean speech and noise (MS-SNSD plus paid sets)… | ||
| How to Publish Your Own Web 3.0 Health Solutions | Ahmed, Viktoria | 29m |
Solve.Care platform shows a concrete path to publish Web3 health apps: users author networks in minutes via care labs Imaginarium, define roles and journeys… | ||
| Hedonometry and Big Data | Muthu Ramachandran, Petar Kocovic | 41m |
Petar Kocovic and Muthu Ramachandran explained to us: the workings of a hedonometer and its applications such as looking into the most frequently used positive… | ||
| Using AI to solve complex business problems: optimizing... | Pietro Quaglio | 16m |
Lockdown-driven inventory surpluses force a move from heuristics to automation: a prescriptive pipeline combines elasticity‑demand models and full‑price demand… | ||
| The world in 2029 | Lars Rinnan | 36m |
Claims that by 2029 a $1,000 computer reaches 10^16 calculations/sec—brain-level compute—enabling cheap AI that can eliminate poverty, famine and disease… | ||
| Latest Techniques of Entity Matching in NLP | Avinash Pathak | 30m |
Explains that end-to-end entity matching uses blocking to cut pairwise comparisons dramatically — e.g., a 10-record example drops from 45 expensive comparisons… | ||
| On the Aspects of AI and Robotic Autonomy | Pushan Kumar Dutta | 30m |
Argues that autonomy in targeting is a software function and that today’s remote‑controlled weapons can become autonomous with a software upgrade, so software… | ||
| Comparison Analysis of FB Prophet, Amazon DeepAR+ & CNN-QR Algorithms | Emir Zunic | 29m |
Real-world retail sales from a 5,081‑item portfolio (400 active, top 200 ≈90% turnover) are backtested 12 times monthly to compare Facebook Prophet, Amazon… | ||
| Amazing things that happen with Human-AI synergy | Petar Velickovic | 36m |
Researchers show graph neural networks embedded in Google Maps yield travel-time predictions that cut error by over 40% in some cities (Sydney). A GNN flags an… | ||
| Land Boundary Delineation using U-Nets | Theodophilus Aidoo | 21m |
A segmentation pipeline uses U-Net with ResNet34 encoder pretrained on ImageNet to learn parcel boundaries from Sentinel-2 RGB (B2,B3,B4) tiles (2017), with… | ||
| New Paradigm for Building AI & Data teams | Alex Linc | 29m |
Argues a human-centric hiring model that accepts churn and aims to have people return over a 10 year span while growing skills on live projects, not hiring… | ||
| ML applications in healthcare - Saudi Arabian hospital case study | Amibath Saxena | 20m |
Case studies use logistic regression, SVM and mention random forests applied to real hospital data and deployed in production. Logistic regression predicts… | ||
| Crop classification using NDVI | Bright Aboh | 22m |
Uses Sentinel-2 10 m imagery from 2019–2021 to build multi‑temporal composites and compute NDVI time series for each field, then fits a harmonic analysis… | ||
| The Making of a Data Organization | Denys Holovatyi | 31m |
Summarizes patterns found across 37 data projects covering about $350B of client revenue and prescribes a reproducible setup: a data strategy plus an Operating… | ||
| Skills for Data & AI Managing positions | Josip Saban | 30m |
First-week checklist with concrete steps: learn where the team and projects came from, meet the team and hold 30-minute one-on-ones, meet the boss and gather… | ||
| Avoid mistakes building AI products | Karol Przystalski | 31m |
Claims that 85% of AI projects fail and ten case studies show why: dataset bias makes a husky be identified by snow background, a Tesla crash traces to… | ||
| Why we pulled the plug out of a perfect working AI Model | Martijn Baunters | 23m |
Builds a classifier that assigns per-attendee no-show probabilities and surfaces ranked lists; on one campaign it outputs a 2000-person list with ~75% no-shows… | ||
| How can product curiosity help to have more successful AI/Data teams? | N.Tahmasian | 19m |
Only 13% of data science projects reach production, so the recommendation is concrete: build cross-functional skills, start with the voice of the customer not… | ||
| Accelerating drug research with AI and cloud computing | Ognjen Milicevic | 29m |
Budget-conscious RNA‑seq planning recommends using paired design to reduce inter‑individual variation and absorb batch effects, at the cost of halving degrees… | ||
| Business Value through XAI | Ozgur Akarsu | 20m |
Retail demand-forecasting pipeline produces 44k weekly forecasts for four‑ and 20‑week horizons across 70,000 SKUs (262 categories) using >200 features… | ||
| Don't Stop at Data Democratization! | Alexandra Ebert | 17m |
Generative AI creates structured synthetic data that breaks one-to-one links to real people while preserving correlations and time dependencies so models… | ||
| The NextGen AI Festival | Anica Pavlovic | 16m |
A Belgrade-based program runs hands-on STEM workshops for ages 3–19 that combine LEGO and electronics with block and text programming so kids build a robot… | ||
| ML will transform Creativity forever. Are you ready? | Apolinario Pasos | 25m |
Text-to-image systems like DALL·E and Stable Diffusion are only the start: open source release plus the diffusers library enables community extensions such as… | ||
| Learning Data Science through Education, Bootcamps & MOOC | B.Urosevic, G.Milovanovic | 47m |
A new Master of Computational Finance combines finance, computer science, machine learning and blockchain and accepts a Python and R bootcamp prep before two… | ||
| A new wave of Network Science - from fantasy to applications | Milan Janosov | 28m |
Constructs social maps from raw text by tagging every sentence mention and turning characters into nodes and co-mentions into weighted edges, processing ~5… | ||
| Understanding the nature of Bias in Natural & AI Systems | Nisheeth Vishnio | 42m |
Defines bias as different treatment of groups, models it as a scaled-down perceived utility, and runs a stylized hiring model with 100 candidates (50/50… | ||
| Myth & Truth behind Artificial General Intelligence | Peter Morgan | 31m |
Claim: current deep learning on GPUs and TPUs cannot produce AGI because it is statistical and power-hungry; building AGI requires neuromorphic processors that… | ||
| Panel: Generative art for 21st century | Rebecca Aston, Thorsten Wiedemann | 36m |
Argues that generative art without computers is real — rules, chance and Pollock-style systems count — while current AI tools (DALL·E, Midjourney, Stable… | ||
| The nuts and bolts of music source separation | Stipe Kabic | 14m |
An in-depth run-through of music source separation explains that audio has 44,000 samples per second making datasets terabytes large, and separation must… | ||
| Panel: AI Feminism | Tatjana Kecojevic, Roxena Adam | 44m |
Panel argues that AI adoption needs practical education across ages: teach kids robotics to build creative and collaborative thinking, run mentoring like… | ||
| Clinical Development in a Post-pandemic world | Raj Modi | 19m |
Oracle Health Sciences presents a unified cloud platform that links EHRs (post‑Cerner acquisition), wearables and genomic pipelines to speed trials and… | ||
| Intersection of International Relations and AI | Kay Firth Butterfield | 51m |
Identifies three concrete regulatory models: the EU AI Act that aims to export GDPR‑style rules, a fragmented US approach that repurposes existing law (Civil… | ||
| How to bridge the gap between Data Scientist & Decision Makers? | Rajeev Sharma | 34m |
Argues that success means shipping models into workflows, not just accuracy, and recommends starting with workshops, pairing with product/BA/UX, and building a… | ||
| Panel: How to learn Data Science from books? | Mario Meir-Huber, Wolfgang Weidinger, Stefán, Danko Nikolic | 46m |
Community-written handbook unpacks concrete tradeoffs: machine learning scales poorly (empirical power laws imply roughly 500× resources per doubling of… | ||
| The (Swiss cheese) data conundrum... | Alicia Montoya, Nairman Maddah | 23m |
Swiss Re Institute builds C.H.E.E.S.E. (Company Hierarchy End‑2‑End Structure Extraction) to join internal and purchased datasets, claiming unique company… | ||
| How Bosch Power Tools leverages User Data and AI... | Pooja Bhatia, Nina Rsumovic | 23m |
Bosch Power Tools crawls reviews from 150 e‑shops, aggregates ~160k labeled docs, translates everything to English with Azure cognitive services, and runs a… | ||
| Why you need to think about MLOps at the beginning of your project | Dmitrii Fursov | 22m |
A practical roadmap that argues for building MLOps from day one with concrete tradeoffs: projects that skip it hit one month refactor surprises when notebooks… | ||
| How Big Data can foster development | Drasko Draskovic | 34m |
UNDP Accelerator Labs use satellites, mobile operators and social platforms to produce near–real-time policy signals: Meta Facebook social connectedness index… | ||
| The geometry of Intelligence in a Large Question-Answering System | Miodrag Vladic | 26m |
Claims a production question‑answering engine that encodes text as 256‑dimensional vectors and ranks by angular distance and eigenvector‑based subspace… | ||
| Similarity search: Take your search engine to the next level | Francisco Losada | 26m |
Explains how images become 1000‑dimensional feature vectors via a CNN (example ResNet pretrained on ImageNet) converting ~1M+ pixel RGB arrays into compact… | ||
| Why is a good data scientist a package of professions? | Neza Strus | 22m |
Argues that data scientists must combine technical work with advocacy, design and negotiation, showing concrete fixes: add average active days per day since… | ||
| What is Audio Data Augmentation? | Djordje Grozdic | 26m |
Covers concrete augmentations (time shifting by milliseconds, time stretching, pitch scaling to child or deep voices, white‑noise addition, convolutional… | ||
| Transformers for extractive text summarization | Anton Guldinskii | 31m |
Builds an extractive summarizer for a corporate Data Lake using pretrained Transformers (BERT/RoBERTa variants) plus a small sentence-level Transformer… | ||
| Machine learning algorithms as tools for student success prediction | Dijana Oreski | 25m |
Applies supervised ML (decision trees, k‑NN, neural nets, Bayesian) to 400 students across three generations combining Moodle logs, surveys and YouTube… | ||
| Future of Data Education | Jose Portilla | 44m |
Claims that data science needs its own undergraduate major and that education must merge scalability with personalization drive the recommendations… | ||
| Reverse Engineering Cloud Native: Interoperability and Community | Katie Gamanji | 31m |
Reverse engineers cloud native growth into concrete cause and effect: interfaces (CNI/CRI/CSI/SMI/Cluster API) enable the ecosystem, not hype. Cites adoption… | ||
| Riddles in Supply Chain Management - How AI solves them? | Nino Pozar | 26m |
Shows an end-to-end system that uses demand forecasting with ML (feature engineering: holidays, weather, promotions, outlier and stockout handling), computer… | ||
| Starting deep learning projects without enough labelled data | Sergei Smirnov | 30m |
Starts models from shortcuts: uses a pre-trained detector class (a clock from COCO) to localize dartboards, trained Faster R-CNN on ~50 labeled images and gets… | ||
| AI & ML in tailored software for decision-making purposes | Vladimir Rakic | 29m |
Claims deployment of EBIS smartcopics (aka smart capex): a data‑lake pipeline ingests OSS KPIs, network topology, vendor configs, CRM forecasts and optional… | ||
| AI for Autonomous mobile robots | Valentina Zadrija | 26m |
Company builds a working tray autonomous forklift that unloads trailers using vision only, no GPS, running semantic and instance segmentation, on-camera stereo… | ||
| Machine-Brain Intelligence in Brain-Computer Interfaces | Jelena Mladenovic | 36m |
Claims that closed‑loop EEG BCIs require mutual adaptation: humans learn to produce signals while the decoder recalibrates online, typically after a 10 minutes… | ||
| Show Me Your MVP! | Liliya Akhtyamova | 27m |
Claim: data scientists can own product demos without front-end work by building cloud‑hosted interactive prototypes that stakeholders can exercise and… | ||
| AI in Sports - Basketball Rule Violation Detection | Mladen Canovic | 29m |
Enetel Solutions builds a Basketball Rule Violation Detection System (in collaboration with Professor Dr Vladimir Lučić) that detects pivot/travel violations… | ||
| Providing transparency about the gender visibility in newspapers | Dominic Herzog | 34m |
TX Group runs a daily Equality Alert that measures gender visibility in images and text by inferring gender from first names, registered users, or reading… | ||
| Data as an instrument for more efficient collaboration with robots | Kosta Jovanovic | 31m |
Lab builds and tests stiffness-controllable actuators that let cobots modulate joint compliance, combines vision, IMUs and EMG to predict human motion and… | ||
| Let's talk about Recommendation Systems! | Mihailo Joksimovic | 32m |
Covers how recommendation systems go from a sparse user‑item matrix to filled predictions using matrix factorization (SVD/PCA) after the Netflix Prize… | ||
| Building the future, a founder's perspective | Ben Taylor | 45m |
Built and sold an AutoML deep‑learning company and then joins DataRobot after an acquisition; argues industry has an 85% failure rate because models rarely… | ||
| AIOPS – How can machine learning help in IT operations | Damir Kopljar | 02m |
Company Cross AI builds a production AIOps pipeline for a large Croatian telco that combines big data ingestion, ML models for anomaly detection and alert… | ||
| BI Toolkit Powered by Natural Language Processing | Sandra Martincic Ipsic | 20m |
Prototype wraps PDF-to-text and machine translation into English, uses YAKE keyword extraction to compress documents, then two Random Forest classifiers (one… | ||
| Official Opening | Alex Linc | 06m |
Organizers describe months of overnight work to put on an in‑person conference in Belgrade on November 17, 2022, thanking named team members and a partner… | ||
| AI-supported transformation of the urban infrastructure | Hrvoje Novak, Vinko Lesic | 31m |
Holistic control stacks combine model predictive control with ML forecasts for zones, HVAC and microgrids, running as modular software modules that coordinate… | ||
| Ethical AI & AI Quality by Design | Muthu Ramachandran | 43m |
Volunteering research persuades standards bodies and British Computer Society to start an AI quality standard and publishes principles and an assessment… | ||
| Combining behavioral research & NLP to combat gender biases | A. Mosa, M. Tkacik | 31m |
A prototype called Bias Eliminator app highlights masculine/feminine-coded words (using a 2011 gold‑standard 150-word list) and suggests context‑aware… | ||
| How can we make the most of Ethics applied to AI? | Emmanuel R Goffi | 47m |
Argues that AI is more a social symbol than an autonomous agent and that ethics must be operational not cosmetic, citing an IBM/Oxford survey of 14,000 where… | ||
| Key practices to improve your data communication | Maxim Gorbachevsky | 34m |
Shows that a clear claim — charts must convey insight without extra words — drives every choice: a baby-name chart reveals post-hurricane declines; simply… | ||
| Delivering Delivery Time Prediction | Aid Ahmetovic | 26m |
Built a delivery ETA service for Douglas using historical warehouse and carrier data to predict up to five business days, improving on a poor regression… | ||
| Next-Wave of Value – Operating Model for Scaling Data Science & AI | Michael Soucek | 25m |
A 1,200 C-level survey finds widespread pilots but only 12% scale successfully; the common winners combine a C-level AI strategy, a validated cloud data… | ||
| Reproducibility and versioning of ML systems | Spela Poklukar | 32m |
Explains exactly what must be versioned to reproduce results: dataset id and timestamp, train/test split and shuffling, preprocessing and feature transforms… | ||
| Testing Machine Learning Systems: What it is and why you should care | Nina Mrzelj | 32m |
A real project builds a smart-quotation pipeline for custom automotive parts that chains OCR, NER, feature extraction and several models (visibility, step… | ||
| DataOps as a Service | Dimitra Petrova, Antoni Ivanov | 24m |
Company builds an open‑source framework called Versatile Data Kit that combines a Python SDK and a managed control service to put data jobs into production… | ||
| There is no such thing as Artificial Intelligence | Luc Julia | 47m |
Claim: there is no single “artificial intelligence” but many narrow tools. Traces history from Pascaline (1642) through 1956 Dartmouth, expert systems, machine… | ||
| Bank evolution to data science-driven business model | Miroslav Grbović | 35m |
Banca Intesa Belgrade moves CRM from sales-force heuristics to production ML-driven campaigns, building bespoke binary classifiers in Python ML models for each… | ||
| How to boost data science routines with DataArt’s AutoML Platform? | DmitryBaykov | 28m |
Claims an AutoML platform that performs Automated Feature Engineering on relational (SQL) data, auto-detects types across up to five to seven joined tables… | ||
| Use case in demand forecasting | M. Mozina, P. Hajdukovic | 28m |
DataLab builds a cloud pipeline on Google Cloud using BigQuery, Vertex AI and Python to produce 5 million forecasts/day for a 90-day horizon across ~200 fresh… | ||
| Bridging the gap between AI Research and Human-Centered Products | Andreja Ilić | 45m |
Proofs of concept often fail in production because of concrete gaps: an Excel Data from picture scanner ships but needs bounding‑box UX and human correction to… | ||
| Lakehouse Architecture with Delta Lake and Databricks | Dragan Beric | 28m |
Lakehouse built on Delta Lake and Databricks uses Delta files plus a Delta log that provides Delta log checkpoints after 10 commits enabling metadata scaling… | ||
| Govern Your Event Stream | Ivan Dundovic | 30m |
CROZ builds a small Java glue that reads Kafka audit logs and schema registry entries and creates topics, schemas and lineage in Apache Atlas in near real… | ||
| Fostering the new data culture at Bosch Power Tools | Christopher Wiess | 40m |
Bosch Power Tools describes concrete wins: an Azure cloud data hub centralizes pipelines, a 200‑person data ambassador bootcamp spreads analytics skills, and… | ||
| Smart approach in development and deployment process for ML models | Danijel Ilievski | 24m |
Claims that 80% of time is spent on data preparation and that a smart generic data mart (ADS) cuts go‑to‑production time by enabling fast prototyping and… | ||
| The ML system endeavors | Stanko Kuveljic | 32m |
A computer vision pipeline built for smart buildings captures fisheye ceiling video, runs object detection and tracking on AWS (hundreds of ms per frame, ~5s… | ||
| Container Tracking for Bosch Tools Supply Chain Operations | N. Vukovic, M. Ivanovic | 28m |
Model combines daily AIS snapshots (since Nov 2021) with static route features to predict vessel ETA for 2,000 trips from Asia Pacific to Western Europe, using… | ||
| Developing Visual AI Solutions for Online Marketplace | Mladen Fernezir | 29m |
Velebit AI builds end-to-end visual features for marketplaces that run in production not just in papers: a classifier calibrated with temperature scaling and a… | ||
| Why Synthetic Data is needed for AI Fairness and Explainability | P.Tiwald, A.Kalam | 47m |
Argues synthetic tabular synthetic data can unlock locked datasets for product development and privacy, with a startup workflow used by banks, insurers and… | ||
| Application of AI in modern production robotics | Marko Tanaskovic | 29m |
Claims AI can replace human camera operators by combining image-analysis software with IP‑controlled production robots; built pan‑tilt heads and rail platforms… | ||
| Face spoofing detection: theory and practice | Pavle Milošević | 28m |
Covers practical pipeline: early detectors use LBP+SVM and color histograms or image‑quality metrics to spot print or screen artifacts, while modern systems… | ||
| How to train GPT-3 with your own dataset | Heiko Hotz | 30m |
GPT-3 (175 billion parameters) gets fine-tuned via the OpenAI API using a JSONL dataset; a 5,000-document corpus yields prompts but fine-tuned with a few… | ||
| Towards the Universal Law of Robustness for Deep Neural Networks | Luka Nenadović | 28m |
Claims that overparametrization is necessary for robustness, showing memorization requires roughly 2n/d neurons and that smooth (Lipschitz-bounded) networks… | ||
| Analysis of sports scenes using computer vision models | Marina Ivasic Kos | 27m |
Recorded a handball dataset of ~4 hours from three GoPro/action cameras with players aged 14–17 and train models end to end: Mask R-CNN and YOLO for player… | ||
| The Challenges of Product Analytics | Tamas Spancik | 19m |
Argues there are no one-size-fits-all rules for product analytics and lists concrete traps: attractive but not actionable metrics, unclear ownership, and… | ||
| Combining behavioral research and NLP to combat gender biases | A.H.Mosa, M. Tkacik | 31m |
Built a live bias Eliminator app that highlights ~150 gender-coded words and suggests context-aware swaps using a Roberta masked LM with a double-mask prompt… | ||
| The ways AI will change your workplace | Iliada Evangelia Kothra | 25m |
Claims that 95 million jobs will involve AI, backed by a personal platform built to help Greek brands livingpostcards.com, and concrete tools like IoT sensors… | ||
| Optimizing Cloud Costs with Machine Learning - A CloudVane Story | Dario Radecic | 24m |
A multi‑cloud management platform that forecasts daily and monthly costs, detects anomalies and recommends right‑sizing, claiming up to 40% savings on some… | ||
| How to Build a Data-Intelligence Startup within your Organization | A.Cuvitillo | 23m |
Claims that scaling data inside legacy firms requires a shared data platform (data as the core, not ERP) plus a data center of excellence embedding analysts… | ||
| Applications of AI in news and media | Danijela Horak | 24m |
BBC converts 100 years of HD-equivalent material into searchable text and tags, running an in-house transcription pipeline because third-party costs are… | ||
| Implementing effective Data Strategy in organisation | Branko Kovac | 27m |
Argues that a data strategy does not require a half‑million budget and can begin with 10, 100 or 15,000; prioritises people over tech, then lists concrete… | ||
| Innovation enabling - for Bosch eBikes | Pawel Piekut | 22m |
Bosch eBike backend migrates from a private corporate cloud to AWS because private infrastructure hits scalability limits, creates knowledge silos and causes… | ||
| How to enable enterprises for DevSecOps without fighting the silos | S.Kister | 35m |
Audi creates a Kubernetes competence center that starts with passionate engineers, not processes, then automates and scales a platform portfolio across VW… | ||
| Multi-agent AI Systems | Livio Benchick | 40m |
A multi-agent platform hosted on Azure that runs lightweight personalized agents is used to build real products like Maggie hypertension pilot, which enrolled… | ||
| Engineers guide for shepherding models in to production | Marko Dimitrijevic | 31m |
Checklist for production: define all model inputs and outputs and document ambiguous fields like location, plan for incomplete or dirty live data, and choose… | ||
| Overview of the Databricks Platform | Petar Zecevic | 34m |
Databricks presents a unified Data Lakehouse used by more than 7,000 organizations with over 3,000 employees and ~$3B funding, combining data warehouse BI and… | ||
| ENIRISST | Christos Tryfonopoulos | 30m |
This talk presented ENIRISST, an intelligent research infrastructure for shipping, supply chain, transport and logistics, and focused on the vision, the… | ||
| Voice fingerprinting & recognition | Tomislav Krizan | 20m |
Baseline uses wav2vec then moves to modified Whisper (OpenAI Whisper pretrained on ~6,680,000 hours) with injected voice fingerprinting layer plus… | ||
| Anti-Money Laundering ML Modelling Approach | Gizem Akar | 18m |
Raiffeisen builds an unsupervised AML system that profiles customers (static + monthly dynamic features), creates peer-group comparison, and flags outliers… | ||
| REDLake Azure - Enterprise Data Lake and Business Satellites | Predrag Ilic | 24m |
REDLake Azure is Bosch’s global cloud data repository that consolidates 700+ TB from SAP, ERP and cloud sources into a zone model on ADLS Gen2, ingests and… | ||
| Disrupting Supply Chain with Data Science | Arthur Jansen | 26m |
Company builds a B2B product that crawls company websites to reverse‑engineer client–supplier links, using NLP transformers to detect customer pages and… | ||
| From ethics to law in the metaverse: recommender systems as common good | Lj.Bojic | 23m |
Research group documents describe measured increases in addiction intensity from radio to smartphone and find addictive intensity higher in VR, citing VR games… | ||
| Machine Learning with Google Cloud Platform | Tiago Henriques | 32m |
Overview of concrete Google Cloud ML capabilities: managed Vertex AI for notebooks, training (Docker containers), model registry and endpoints; a feature store… | ||
| Practical experience of implementing Data Mesh in the air transport industry | Bojan Sovilj, Ivan Karlovic, Boban Davidovic | 48m |
Eight months into a Data Mesh rollout for a Scandinavian low‑cost airline the team moves transactional data via DMS CDC to S3, catalogs it with Glue and Lake… | ||
| Algorithmic Transparency and Accountability | Branko Primetica, Natali Delic, Drazen Orescanin | 46m |
Panel compares concrete laws and company practices: EU draft Article 52 and US proposals (Filter Bubble, Algorithmic Accountability) versus Canada’s… | ||
| Data 4 Development | Bogdan Stesevic, Dubravko Ćulibrk, Jelena Ruzicic | 28m |
Government builds a state secondary data center and a national AI platform with a supercomputer installed about a year ago, used to coordinate COVID… | ||
| nothing matches | ||