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Addressing AI Trust, Systemic Bias & Transparency as Business Priorities

Our friend Dr Stuart Battersby, CTO of Chatterbox Labs (an Enterprise Al Company), reached out to us to share how his company built a patented AI Model Insights Platform (AIMI) to address the lack of explainability & trust, systemic bias and vulnerabilities within any AI model or system.

KDD 2020 Celebrates Recipients of the SIGKDD Best Paper Awards

KDD 2020, the premier interdisciplinary conference in data science (which took place virtually Aug. 23-27, 2020), announced the recipients of the SIGKDD Best Paper Awards, recognizing papers presented at the annual SIGKDD conference that advanced the fundamental understanding of the field of knowledge discovery in data and data mining. Winners were selected from more than 2,000 papers initially submitted for consideration to be presented at the conference.

Video Highlights: How to Set Up a Remote Data Science Team

The talk below was part of a joint webinar with Appsilon and RStudio on July 28, 2020. In the presentation, Appsilon Senior Data Scientist Olga Mierzwa-Sulima explains best practices for data science teams – whether they are working in the office together or fully remote.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2020

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

The State of Data Management – Why Data Warehouse Projects Fail

Based on new research commissioned by SnapLogic and conducted by Vanson Bourne, who surveyed 500 IT Decision Makers (ITDMs) at medium and large enterprises across the US and UK, this whitepaper explores the data management challenges organizations are facing, the vital role data warehouses play, and the road to success.

HuBMAP Inaugural Data Release Puts Detailed Anatomical Data about Seven Human Organs at the Service of Scientists, Public

HuBMAP (the Human BioMolecular Atlas Program) has released its inaugural data for use by the scientific community and the general public. Included in this release are detailed, 3D anatomical data and genetic sequences of healthy tissues from seven organ types, at the level of individual cells as well as many bulk tissue data sets. HuBMAP’s ultimate goal is to provide the framework required for scientists to create a 3D atlas of the human body.

Video Highlights: BigQuery + Notebooks: Building an Analytics Pipeline on Kaggle

Your architecture choices impact how efficiently you’re able to use your data. In this “Snapshots” video produced by Kaggle, Data Scientist Wendy Kan demonstrates how she incorporates BigQuery and Kaggle Notebooks into her workflow. Watch her create an interactive network analysis graph that explores the most commonly installed Python packages!

Research Highlights: Attention Condensers

A group of AI researchers from DarwinAI and out of the University of Waterloo, announced an important theoretical development in deep learning around “attention condensers.” The paper describing this important advancement is: “TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices,” by Alexander Wong, et al. Wong is DarwinAI’s CTO.

KDD 2020 Showcases Brightest Minds in Data Science and AI

The Association for Computing Machinery’s Special Interest Group on Knowledge Discovery and Data Mining (ACM SIGKDD) will hold its flagship annual conference, KDD 2020, virtually, August 23-27. The KDD conference series, started in 1989, is the world’s oldest and largest data mining conference, and is the venue where concepts such as big data, data science, predictive analytics and crowdsourcing were first introduced.

Big Data Performance Report

To shed light on how IT operations teams are dealing with working in challenging environments, Pepperdata has carried out a period of customer research. This report revealed a wealth of insights regarding the condition of enterprise workloads that lack the benefits of observability and continuous tuning. Combined with cloud computing statistics and a more general understanding of big data industry trends, there is much to learn here about the present and future of the data analytics industry.