In the News
7 Must-Read Books About Artificial Intelligence
In late 2019, we published “7 Classic Books To Deepen Your Understanding Of Artificial Intelligence.” It’s time to run it back. Viewed from this perspective, neural networks are almost as dependent upon human intelligence as are GOFAI [good old-fashioned artificial intelligence] systems.” The...
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In The News
Glossary of Data Science Terminology: A Beginner’s Guide
Data scientists have strong computer science skills, advanced knowledge of statistical models, and strong programming skills. List of Data Science Terms: Things Every Data Scientist Should Know Approximation error Bayesian network Big data Business intelligence Confidence interval Cluster analysis...
AI and Deep Learning Predictions for Finance in 2022 – Trends to Watch from the RE•WORK Community
Recent developments in AI and deep learning have the potential to transform the way that banks and financial services firms do business, including but not limited to customer service, portfolio management, and fraud detection. As we approach RE•WORK’s upcoming London AI Finance Summit on 17-18...
Year-End Review & a glimpse into 2022 from Essentials
As the end of the year approaches, it's time to look back at the fast-changing evolution of AI in 2021. To help you navigate this ocean of information the Faveeo team has prepared a Year-End Review that will help you catch the information that matters the most.
Applied use cases
Could A.I. revolutionize the future of heart health?
Scientists are finding new ways to use A.I. to tackle the biggest health concern in the world. February may be the shortest and coldest month of the year. But for many, it is a time to give special recognition to often overlooked aspects of world history (Black History Month) and recognize what may be the single greatest threat to health in the world. For many, February is also known as Heart Health Month, and 2022 will be the 58th consecutive year it is recognized.
What does the evolution of AI mean for HR?
Digital transformation has accelerated demands for a more diversified and skilled workforce. Rapid changes have highlighted the importance of a back-to-human approach of training, career development, and hiring. 97% of organizations are planning significant transformation this year but feel that inadequate workforce skills and employee burnout may hinder this goal.
The Hybrid to Give Your AI the Gift of Knowledge
Symbolic AI and machine learning/deep learning all have their own set of strengths that, when used together in a hybrid fashion, make for a powerful approach that uniquely supports a number of key enterprise applications going forward. But before we get to that, let’s take a look at what each brings to the table.
RFP - Technology to support data availability for Responsible AI 28 Feb 2022
Outputs expected from the first phase The following outputs are expected from the first phase: ● One or more AI system use cases identified for technology demonstration in future phases, taking into account ○ The extent to which the use case supports one of the three “AI for good” topics of climate...
AI Ethics, Technology, and Reimagining the Future with Gerd Leonhard
Are we living in a dystopia? Futurist Gerd Leonhard joins us to discuss humanity's relationship with technology. As the Metaverse grows, what impact will virtual reality and artificial intelligence have on society? More importantly, how can we build a... Gerd Leonhard website -...
Ethics of robotized public services: The role of robot design and its actions
Public administrations invest heavily in the development of ‘smart’ public services, including autonomous public service robots. Since public service robots are designed to operate unsupervised, robots must interact in an ethically acceptable way with citizens.
An Autonomous Task Assignment Paradigm for Autonomous Robotic In-Space Assembly
This will includes a job shop type formulation to discretize and articulate the steps needed to complete an assembly, precedence constraints to ensure tasks are completed in the required order, continuity constraints and machine validity constraints to ensure that the correct machines are used on...
The case against tomorrow's robots looking like people
Numerous psychological studies by Clifford Nass and his team at Stanford University showed that when computers are designed to be like humans, users respond and engage in socially appropriate ways. Getting beyond the human teammate idea may increase the likelihood that designers will take advantage...
Robots that play active roles in our lives don’t need to look like us
This is part of a larger project from Riken, called the Guardian Robot Project, the goal of which is “to develop an autonomous robot that can be close to people and make people feel the ‘heart.’ Once such a robot is realized, it will be accepted by people and will play an active role in every aspect...
SEER 10B: Better, fairer computer vision through self-supervised learning on diverse datasets
With 10B parameters, SEER outperforms other models on important fairness benchmarks recently proposed by Meta AI Research. On top of achieving strong performance on standard computer vision benchmarks (for example, 85.8 percent top-1 accuracy on ImageNet), the model also excels at challenging tasks...
The Stanford Natural Language Processing Group
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers Krishna Pillutla, University of Washington Venue: Zoom (link hidden) Abstract As major progress is made in open-ended text generation, measuring how close machine-generated text is to human language remains a...
A Decade of Deep Learning: How the AI Startup Experience Has Evolved
He earned his PhD from Stanford working on NLP (natural language processing) before co-founding an AI startup called MetaMind in 2013. In this interview, Socher discusses a number of topics, including: how things have changed for AI startups in the last decade; the differences between doing AI in...