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Crime forecasting: a machine learning and computer vision approach to crime prediction and prevention

Circa 2021


A crime is a deliberate act that can cause physical or psychological harm, as well as property damage or loss, and can lead to punishment by a state or other authority according to the severity of the crime. The number and forms of criminal activities are increasing at an alarming rate, forcing agencies to develop efficient methods to take preventive measures. In the current scenario of rapidly increasing crime, traditional crime-solving techniques are unable to deliver results, being slow paced and less efficient. Thus, if we can come up with ways to predict crime, in detail, before it occurs, or come up with a “machine” that can assist police officers, it would lift the burden of police and help in preventing crimes. To achieve this, we suggest including machine learning (ML) and computer vision algorithms and techniques.

An Automated System for Crime Investigation Using Conventional and Machine Learning Approach

Circa 2019


Crime causes significant damage to the society and property. Different kinds of physical or direct methods are devised by the law and order department to spot out the criminals involved in the crime. This techniques will explore the evidences at crime site. For instance if it finds a fingerprint then the system will capture and send it to forensic department for fingerprint matching, which can be later used for identifying the suspects or criminals by investigations etc. Yet, it is a huge challenge for them to find the criminal due to less or no evidence and incorrect information, which can change the direction of investigation to the end. This paper proposes a data analysis approach to help the police department by giving them first-hand information about the suspects. It automates the manual process for finding criminal and future crime spot by using various techniques such as pattern matching, biometric and crime analytics. Based on the availability of information, the system is able to produce the expected accuracy.

Deploying Artificial Intelligence At The Edge

From ecosystem development to talent, much effort is still required for practical implementation of edge AI.

By Pushkar Apte and Tom Salmon

Rapid advances in artificial intelligence (AI) have made this technology important for many industries, including finance, energy, healthcare, and microelectronics. AI is driving a multi-trillion-dollar global market while helping to solve some tough societal problems such as tracking the current pandemic and predicting the severity of climate-driven events like hurricanes and wildfires.

FedEx, Aurora to launch autonomous-truck routes in Texas

FedEx Corp. and self-driving vehicle startup Aurora Innovation Inc. are launching a pilot program for autonomous-truck shipments between Dallas and Houston, with the companies announcing Wednesday what they called a first-of-its-kind partnership involving the two companies and a truck maker.

“This is an exciting, industry-first collaboration that will work toward enhancing the logistics industry through safer, more efficient transportation of goods,” said Rebecca Yeung, vice president of advanced technology and innovation at FedEx FDX,-9.12% 0 in a news release.

I Tried Warning Them — Elon Musk on Superhuman AI

I tried to warn them.-Elon Musk.


Elon Musk has warned humanity many times about the dangers of superhuman AI. He thinks the advent of digital superintelligence will bring about profound changes to human civilization. Elon Musk thinks the technological singularity could either be super beneficial or it could be terrible for our society. Elon said that no one knows for sure the impact superhuman AI will have on our world but that one thing is for certain: We will not be able to control it. He thinks artificial intelligence will be used as a weapon and warns that the lack of AI regulation could mean it’s already too late for humanity.

Elon Musk now has adopted a “fatalistic” attitude towards the AI control problem because he feels that nothing is being done to try to mitigate the negative effects of future AI systems.

The reasonable concern about a possible extinction level event from digital Superintelligence stems from the period of time in which Narrow AI achieves artificial general intelligence. Where presumably in this time frame we can do something to stack the odds in our favor.

Today, right now, with our seemingly endless desire for better, faster and cheaper technology, we are collectively contributing in building future AI systems. Whether we are aware of it or not. As Elon Musk put it: We are the biological bootloader for AI.

Novel device for exploratory imaging enables about 1,000 times more access to brain tissue

Science is examining the brain’s neural activity for applications ranging from innovative therapies for brain-related injuries and disease to computational learning architectures for artificial intelligence and deep neural networks.

A research team has developed a tool that lets researchers see more of a live mouse’s brain, to make discoveries that can advance research into the neural circuit mechanisms that form the underlying behavior of the human brain. The tool overcomes the drawback of traditional brain probes—the small amount of tissue they can access, which limits their ability to image neurons of interest.

The innovation is to insert an imaging probe with side-viewing capabilities into a previously inserted optically matched channel—an ultrathin-wall glass capillary—to convert deep brain imaging into endoscopic imaging. The operator can freely rotate the probe to image different , getting a 360-degree view for imaging along the entire length of the inserted probe. This large-volume imaging enables an increase of about 1,000 times in access volume, compared with what is available for imaging at the tip of typical miniature imaging probes.

GSK teams with King’s College to use AI to fight cancer

The pharmaceuticals firm GSK has struck a five-year partnership with King’s College London to use artificial intelligence to develop personalised treatments for cancer by investigating the role played by genetics in the disease.

The tie-up, which involves 10 of the drug maker’s artificial intelligence experts working with 10 oncology specialists from King’s across their labs, will use computing to “play chess with cancer”, working out why only a fifth of patients respond well to immuno-oncology treatments.

New Artificial Intelligence Tool Accelerates Discovery of Truly New Materials

The new artificial intelligence tool has already led to the discovery of four new materials.

Researchers at the University of Liverpool have created a collaborative artificial intelligence tool that reduces the time and effort required to discover truly new materials.

Reported in the journal Nature Communications, the new tool has already led to the discovery of four new materials including a new family of solid state materials that conduct lithium. Such solid electrolytes will be key to the development of solid state batteries offering longer range and increased safety for electric vehicles. Further promising materials are in development.

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