IBM’s Squawk Bot AI helps make sense of financial data flood

In our recent work, we detail an AI and machine learning mechanism able to assist in correlating a large body of text with numerical data series used to describe financial performance as it evolves over time. Our deep learning-based system pulls out from large amounts of textual data potentially relevant and useful textual descriptions that explain the performance of a financial metric of interest – without the need of human experts or labelled data.
The post IBM’s Squawk Bot AI helps make sense of financial data flood appeared first on IBM Research Blog.

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Applications of Artificial Intelligence in Fire & Safety

Being a student secretary of the Fire and Security Association of India at my college, I have conducted various surveys and workshops on methodologies to avert the dangers caused due to fire. As an AI enthusiast, I have always aspired to come with innovative solutions to tackle such issues. My experience in the fire and safety domain with competence in building AI solutions motivated me to think of possible solutions to tackle problems faced by the fire department.

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$400M in C2 funding raised by automotive AI Chip vendor Horizon Robotics

Horizon Robotics, a Chinese automotive AI chip startup that is developing specialized, complex chips for use in autonomous vehicles, has raised another $400 million in its latest C2 round of funding. That’s on top of $150 million in C2 funding that it secured earlier in December, according to the company, bringing its total C2 funding so far to $550 million. Horizon Robotics had announced late in 2020 that it was pursuing a total of $700 million in C2 round funding.

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The future of commercial Deep Learning

How do we balance its benefits and integrity going forward? Underlying modern AI is deep learning, algorithms through which computers learn to perform intelligent tasks without being explicitly programmed. These algorithms train artificial neural networks, which iteratively learn relationships between inputs and outputs through copious examples. My solution to preserving the benefits of commercial deep learning while prioritizing its integrity is three-fold:

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AI-based Recycler AMP Robotics gains $55M in new funding from Investors

AMP Robotics Corp., an AI startup developing technology that sorts recyclable materials, has raised an additional $55 million in its latest funding round. The Denver-based AI startup launched in 2015 has so far raised more than $71 million in two funding rounds.

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AI vs. Human: A comparison of human perception with Artificial Intelligence (AI)

Human intelligence is based on a fantastic duality (a) perception of patterns (b) rational and structural decisions. Both properties are distinct yet complementary to each other and run parallel in the decision-making process of humans. A Machine learning (ML) based system also has two similar structures.

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Deep Science: Using machine learning to study anatomy, weather and earthquakes

Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect the most relevant recent discoveries and papers — particularly in but not limited to artificial intelligence — and explain why they matter.

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Using Reinforcement Learning to build a Self-Learning grasping Robot

In this post, I will explain my experience over the course of a year of working with Reinforcement Learning (RL) on autonomous robotics manipulation. It is always hard to start a big project which requires many moving parts. It was undoubtedly the same in this project. I want to pass the knowledge I gathered through this process to help others overcome the initial inertia.

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15 Free Data Science, Machine Learning & Statistics eBooks for 2021

We present a curated list of 15 free eBooks compiled in a single location to close out the year. Among other articles highlighting such materials, I have written a series of posts since the pandemic erupted, in the case that more people spending more time at home may result in more time for reading.

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A complete Learning Path to Data Labelling & Annotation (with Guide to 15 major Tools)

With the advancements in deep learning algorithms, computer vision and NLP have greatly evolved and done wonders around the world of AI. Along with this AutoML has also grown. This has led many industries to adopt AI smoothly and make efficient use of it in various use cases.

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DeepMind’s big losses, and the questions around running an AI lab

Last week, on the heels of DeepMind’s breakthrough in using AI to predict protein-folding came the news that the UK-based AI company is still costing its parent company Alphabet Inc hundreds of millions of dollars in losses each year. A tech company losing money is nothing new. The tech industry is replete with examples of companies who burned investor money long before becoming profitable. But DeepMind is not a normal company seeking to grab a share of a specific market. It is an AI research lab that has had to repurpose itself into a semi-commercial outfit to ensure its survival.

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Benchmark M1 vs Xeon vs Core i5 vs K80 and T4

Since their launch in November, Apple Silicon M1 Macs are showing very impressive performances in many benchmarks. These new processors are so fast that many tests compare MacBook Air or Pro to high-end desktop computers instead of staying in the laptop range. It usually does not make sense in benchmark. But here things are different as M1 is faster than most of them for only a fraction of their energy consumption.

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Robotic Vision startup Akasha Imaging aims to improve Industrial Manufacturing with AI

With $10.75 million in Series A funding arriving earlier this month, AI robotic vision startup Akasha Imaging is now bulking up its team to ready itself to deliver its nascent AI vision technology to industrial manufacturers by mid-2021.

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5 papers on Face Recognition every Data Scientist should read

Face recognition, or facial recognition, is one of the largest areas of research within computer vision. We can now use face recognition to unlock our mobile phones, verify identification at security gates, and in some countries, make purchases. With the ability to make numerous processes more efficient, many companies invest into the research and development of facial recognition technology. This article will highlight some of that research and introduce five machine learning papers on face recognition. 

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The inevitable symbiosis of Cybersecurity and AI

While improvements in AI and Deep Learning move forward at an ever increasingly rapid rate, people have started to ask questions. Questions about jobs being made obsolete, questions about the inherent biases programmed into the neural networks, questions about whether or not AI will eventually consider humans as dead-weight and unnecessary to achieve the goals they’ve been tasked programmed with.

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The issue of Machine ethics and Robot rights

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence/ robotics communities. We will argue that the attempts to allow machines to make ethical decisions or to have rights are misguided. Instead we propose a new science of safety engineering for intelligent artificial agents.

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Nvidia moves its Software closer to cloud customers through an AWS Storefront

Nvidia is making it easier for AWS cloud customers to find and integrate Nvidia software applications into their AI and deep learning projects through an all-new, all-in-one “storefront” in the AWS Marketplace.

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GE Healthcare lets hospitals test Artificial Intelligence tools

Customers, including radiologists and emergency physicians, will soon be able to try solutions powered by artificial intelligence prior to buying it through GE Healthcare’s Edison Marketplace. GE Healthcare recently announced that it will soon allow customers to find, try, and buy software powered by artificial intelligence (AI) through an online store featuring a range of third-party developers.

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