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Why AI Can't Properly Translate Proust--Yet

Oxford Comp Sci

This observation--that to understand Proust's text requires knowledge of various kinds--is not a new one. We came across it before, in the context of the Cyc project. Remember that Cyc was supposed to be given knowledge corresponding to the whole of consensus reality, and the Cyc hypothesis was that this would yield human-level general intelligence. Researchers in knowledge-based AI would be keen for me to point out to you that, decades ago, they anticipated exactly this issue. But it is not obvious that just continuing to refine deep learning techniques will address this problem.


Artificial Intelligence Discovers Potent Antibiotic

#artificialintelligence

Anewly designed artificial intelligence tool based on the structure of the brain has identified a molecule capable of wiping out a number of antibiotic-resistant strains of bacteria, according to a study published on February 20 in Cell. The molecule, halicin, which had previously been investigated as a potential treatment for diabetes, demonstrated activity against Mycobacterium tuberculosis, the causative agent of tuberculosis, and several other hard-to-treat microbes. The discovery comes at a time when novel antibiotics are becoming increasingly difficult to find, reports STAT, and when drug-resistant bacteria are a growing global threat. The Interagency Coordination Group (IACG) on Antimicrobial Resistance convened by United Nations a few years ago released a report in 2019 estimating that drug-resistant diseases could result in 10 million deaths per year by 2050. Despite the urgency in the search for new antibiotics, a lack of financial incentives has caused pharmaceutical companies to scale back their research, according to STAT. "I do think this platform will very directly reduce the cost involved in the discovery phase of antibiotic development," coauthor James Collins of MIT tells STAT.


Top 6 Deep Learning Models You Should Master for Killer AI Applications

#artificialintelligence

The field of deep learning has gained popularity with the rise of available processing power, storage space, and big data. Instead of using traditional machine learning models, AI engineers have been gradually switching to deep learning models. Where there is abundant data, deep learning models almost always outperform traditional machine learning models. Therefore, as we collect more data at every passing year, it makes sense to use deep learning models. Furthermore, the field of deep learning is also growing fast.


'AI algorithm can predict Alzheimer's disease in 1 minute'

#artificialintelligence

A study by Vuno, a Korean artificial intelligence (AI) developer, showed that a deep learning algorithm could predict Alzheimer's disease (AD) within one minute. Jointly with Asan Medical Center, Vuno verified an AI algorithm using MRI scans of 2,727 patients registered at domestic medical institutions. Vuno found that the algorithm predicted AD and mild cognitive impairment (MCI) accurately. Vuno's deep learning-based algorithm used an area under the curve (AUC) to predict dementia. The closer the AUC value is, the higher the algorithm's performance is.


Artificial intelligence beats us in chess, but not in memory

#artificialintelligence

In the last decades, artificial intelligence has shown to be very good at achieving exceptional goals in several fields. Chess is one of them: in 1996, for the first time, the computer Deep Blue beat a human player, chess champion Garry Kasparov. A new piece of research shows now that the brain strategy for storing memories may lead to imperfect memories, but in turn, allows it to store more memories, and with less hassle than AI. The new study, carried out by SISSA scientists in collaboration with Kavli Institute for Systems Neuroscience & Centre for Neural Computation, Trondheim, Norway, has just been published in Physical Review Letters. Neural networks, real or artificial, learn by tweaking the connections between neurons.


This $39 Python training will prepare you for a future in AI

ZDNet

Artificial intelligence is slowly making its way into every industry, such as transportation and healthcare. Those with the ability to sift through volumes of data to identify insights are best equipped to succeed in an AI-driven job market. If you're interested in a career in AI, then you need to add Python to your skillset. Python is an extremely popular programming language, and it happens to be one of the easiest to learn, especially with The Ultimate Python & Artificial Intelligence Certification Bundle. These expert-taught online courses are normally $199 apiece, but ZDNet readers can grab the set for 97% off, dropping the price to $39.99.


Forgetting in Deep Learning

#artificialintelligence

Neural network models suffer from the phenomenon of catastrophic forgetting: a model can drastically lose its generalization ability on a task after being trained on a new task. This usually means a new task will likely override the weights that have been learned in the past (see Figure 1), and thus degrade the model performance for the past tasks. Without fixing this problem, a single neural network will not be able to adapt itself to a continuous learning scenario, because it forgets the existing information/knowledge when it learns new things. For realistic applications of deep learning, where continual learning can be crucial, catastrophic forgetting would need to be avoided. However, there is only limited study about catastrophic forgetting and its underlying causes.


Recent and forthcoming machine learning and AI seminars: January 2021 edition

AIHub

This post contains a list of the AI-related seminars that are scheduled to take place between now and the end of February 2021. We've also listed recent past seminars that are available for you to watch. All events detailed here are free and open for anyone to attend virtually. This list includes forthcoming seminars scheduled to take place between 15 January and 28 February. Zero-shot (human-AI) coordination (in Hanabi) and ridge rider Speaker: Jakob Foerster (Facebook, University of Toronto & Vector Institute) Organised by: University College London Zoom link is here.


10 Intro Books On AI To Bring You Up To Speed

#artificialintelligence

Artificial Intelligence (AI) has come a long way over the past few years in simulating human intelligence. Today, AI is the lifeblood of almost every organisation cutting across sectors including, retail, financial, healthcare, among others. Here's an updated list of 10 best intro books on artificial intelligence geared towards AI enthusiasts. About: Mathematics and statistics are the backbone of artificial intelligence. This book is perfect for understanding the basics and the mathematics behind AI.


AIs that read sentences can also spot virus mutations

MIT Technology Review

In a study published in Science today, Berger and her colleagues pull several of these strands together and use NLP to predict mutations that allow viruses to avoid being detected by antibodies in the human immune system, a process known as viral immune escape. The basic idea is that the interpretation of a virus by an immune system is analogous to the interpretation of a sentence by a human. "It's a neat paper, building off the momentum of previous work," says Ali Madani, a scientist at Salesforce, who is using NLP to predict protein sequences. Berger's team uses two different linguistic concepts: grammar and semantics (or meaning). The genetic or evolutionary fitness of a virus--characteristics such as how good it is at infecting a host--can be interpreted in terms of grammatical correctness.