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The NBA will use artificial intelligence and a tap-to-cheer app feature to help fans stuck at home get in the game – CNN

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But knowing what a difference their support can make (home court advantage, anyone?) the NBA is proposing a few solutions: a tap-to-cheer app and video technology that will teleport their faces court-side from the comfort of their homes.

"It's obviously very different for the players and it's different for the fans watching at home. I mean, in this sport -- like a lot of others -- there's that home court advantage, that six-man. It's the roar of the crowd, the boos of the crowd," said NBA commissioner Adam Silver Wednesday on CNN with Wolf Blitzer. "We are trying to replicate that to a certain extent without piping in obvious crowd noise."

It's still unclear what kind of difference this technology will make in the overall atmosphere of a sporting match, though.

Not every attempt has been successful, though.

In South Korea, FC Seoul was fined 100 million Korean won (around $81,000) after being accused of placing sex dolls in its stands to add to the atmosphere during a closed match.

CNN's Jack Guy contributed to this report.

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The NBA will use artificial intelligence and a tap-to-cheer app feature to help fans stuck at home get in the game - CNN

$19.9B Artificial Intelligence in Retail Industry, 2027 – Rising Focus on Blockchain and Adoption of 5G Technology – Yahoo Finance

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DUBLIN, July 30, 2020 /PRNewswire/ -- The "Artificial Intelligence in Retail Market by Product, Application (Predictive Merchandizing, Programmatic Advertising), Technology (Machine Learning, Natural Language Processing), Deployment (Cloud, On-Premises), and Geography - Global Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.

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The global artificial intelligence in retail market is expected to grow at a CAGR of 34.4% from 2020 to reach $19.9 billion by 2027.

The growth in the artificial intelligence in retail market is driven by several factors such as the rising number of internet users, increasing adoption of smart devices, rapid adoption of advances in technology across retail chain, and increasing adoption of the multi-channel or omnichannel retailing strategy.

Besides, the factors such as increasing awareness about AI and big data & analytics, consistent proliferation of Internet of Things, and enhanced end-user experience is also contributing to the market growth. However, the high cost of transformation and lack of infrastructure are some of the major factors hindering the market growth during the forecast period.

The study offers a comprehensive analysis of the global artificial intelligence in retail market with respect to various types. The global artificial intelligence in retail market study presents historical market data (2018 & 2019), estimated current data (2020), and forecasts for 2027. The market is segmented on the basis of product, application, technology, retail, end-user, and geography.

Based on product offering, the solutions segment is estimated to command the largest share of the overall artificial intelligence in retail market in 2020. This is attributed to the growing adoption of AI-powered solutions and applications by retailers across the globe to identify personalized customer needs, reduce shrinkage by improving loss prevention at point-of-sale, and enhance customer engagement experience. However, the services segment is estimated to witness rapid growth during the forecast period.

In AI solutions segment, based on product type, the chatbots segment is estimated to command the largest share of the artificial intelligence in retail solutions market in 2020. The large share of this segment is mainly attributed to the growing need to improve customer relationship management (CRM) and an increase in awareness about the advantages offered by chatbots over other customer support options. However, customer behavior tracking is poised to post the fastest growth during the forecast period.

Based on learning technology,the machine learning segment is estimated to command the largest share of the overall artificial intelligence in retail market in 2020. The large share of this segment is mainly attributed to the increasing demand from retailers to track dynamic consumer behavior in order to ensure competitive edge in the retail industry, which has also proved as a key to success of stakeholders in many cases. Moreover, ability of machine learning technology to provide better prediction of sales and customer services, better segmentation of customers, and high personalized product recommendations for advertising and promotions is expected to drive the adoption of machine learning technology during the forecast period.An in-depth analysis of the geographic scenario of the market provides detailed qualitative and quantitative insights about the five regions including North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa. In 2020, North America region is estimated to command the largest share of the global artificial intelligence in retail market, followed by Europe and Asia Pacific. The large share of this region is mainly attributed to its open-minded approach towards smart technologies and high technology adoption rate, presence of key players & start-ups, and increased internet access. However, the factors such as speedy growth in spending power, presence of young population, and government initiatives supporting digitalization is helping Asia Pacific to register the fastest growth in the global artificial intelligence in retail market.

Key players operating in the global artificial intelligence in retail market are Amazon.com, Inc. (U.S.), Google LLC (U.S.), IBM Corporation (U.S.), Intel Corporation (U.S.), Microsoft Corporation (U.S.), Nvidia Corporation (U.S.), Oracle Corporation (U.S.), SAP SE (Germany), Salesforce.com, Inc. (U.S.), and BloomReach, Inc. (U.S.) along with several local and regional players.

Story continues

Key Topics Covered

1. Introduction

2. Research Methodology

3. Executive Summary

4. Market Insights 4.1. Introduction 4.2. Market Dynamics 4.2.1. Drivers 4.2.1.1. Growing Awareness about AI and Big Data & Analytics 4.2.1.2. Adoption of Multichannel or Omni channel Retailing Strategy 4.2.1.3. Need to Enhance the End-User Experience and Improve Productivity 4.2.2. Restraints 4.2.2.1. High Cost of Procurement 4.2.2.2. Lack of infrastructure 4.2.3. Opportunities 4.2.3.1. Increased Adoption of AI-Powered Voice Enabled Devices 4.2.3.2. Growing Number of Smartphones 4.2.4. Challenges 4.2.4.1. Concerns over Privacy and Identity of individuals 4.2.4.2. Lack of Awareness about AI Technology 4.2.5. Trends 4.2.5.1. Rising Focus on Blockchain 4.2.5.1. Adoption of 5G Technology 4.3. Impact of COVID-19 on the AI in Retail Market

5. Artificial Intelligence in Retail Market, by Product Type 5.1. Introduction 5.2. Solutions 5.2.1. Chatbot 5.2.2. Recommendation Engines 5.2.3. Customer Behavior Tracking 5.2.4. Visual Search 5.2.5. Customer Relationship Management 5.2.6. Price Optimization 5.2.7. Supply Chain Management 5.2.8. inventory Management 5.3. Services 5.3.1. Managed Services 5.3.2. Professional Services

6. Artificial Intelligence in Retail Market, by Application 6.1. Introduction 6.2. Predictive Merchandising 6.3. Programmatic Advertising 6.4. In-Store Visual Monitoring & Surveillance 6.5. Market forecasting 6.6. Location-Based Marketing

7. Artificial Intelligence in Retail Market, by Learning Technology 7.1. Introduction 7.2. Machine Learning 7.3. Natural Language Processing 7.4. Computer Vision

8. Artificial Intelligence in Retail Market, by Type 8.1. Introduction 8.2. Online Retail 8.3. Offline Retail 8.3.1. Brick & Mortar Stores 8.3.2. Supermarkets& Hypermarkets 8.3.3. Speciality Stores

9. Artificial Intelligence in Retail Market, by End-User 9.1. Introduction 9.2. Food &Groceries 9.3. Health & Wellness 9.4. Automotive 9.5. Electronics & White Goods 9.6. Fashion & Clothing 9.7. Others

10. Artificial Intelligence in Retail Market, by Deployment Type 10.1. Introduction 10.2. Cloud 10.3. On-Premise

11. Global Artificial Intelligence in Retail Market, by Geography 11.1. Introduction 11.2. North America 11.2.1. U.S. 11.2.2. Canada 11.3. Europe 11.3.1. Germany 11.3.2. France 11.3.3. U.K. 11.3.4. Italy 11.3.5. Spain 11.3.6. Rest of Europe 11.4. Asia-Pacific 11.4.1. Japan 11.4.2. China 11.4.3. India 11.4.4. Rest of the Asia-Pacific 11.5. Latin America 11.6. Middle East & Africa

12. Competitive Landscape 12.1. Competitive Growth Strategies 12.1.1. New Product Launches 12.1.2. Mergers and Acquisitions 12.1.3. Partnerships, Agreements, and Collaborations 12.1.4. Expansions 12.2. Market Share Analysis 12.3. Competitive Benchmarking

13. Company Profiles (Business Overview, Financial Overview, Product Portfolio, Strategic Developments)13.1. Amazon 13.2. Google LLC 13.3. IBM Corporation 13.4. Intel Corporation 13.5. Microsoft Corporation 13.6. Nvidia Corporation 13.7. Oracle Corporation 13.8. SAP SE 13.9. Bloomreach, Inc. 13.10. Salesforce.com, Inc.

For more information about this report visit https://www.researchandmarkets.com/r/3cmz4u

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

Media Contact:

Research and Markets Laura Wood, Senior Manager press@researchandmarkets.com

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$19.9B Artificial Intelligence in Retail Industry, 2027 - Rising Focus on Blockchain and Adoption of 5G Technology - Yahoo Finance

Gatling Exploration to use artificial intelligence to identify possible gold targets at the Larder project in Ontario – Proactive Investors USA &…

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AI experts with Windfall Geotek will use their advanced Computer Aided Resource Detection System to mark targets using pattern recognition and machine learning

Inc ()(OTCQX:GATGF) announced Thursday it will employ artificial intelligence (AI) to identify possible gold targets at the Larder gold project in Ontario.

The company said AI experts with Windfall Geotek will use their advanced Computer Aided Resource Detection System (CARDS) to marktargets which will be evaluated and explored using traditional exploration techniques in upcoming programs.

Gatling's Larder Gold project occupies 3,370 hectares along the Cadillac Larder Lake Break, a prolific structural gold trend. The property hosts three high-grade deposits along the main break, as well as two additional, underexplored gold trends, recently discovered 6 kilometers north.

The company said AI uses pattern recognition and machine learning to make predictions based on compiled datasets. The Larder project benefits from a vast database of recent and historical data, including 2,000 drill holes, 90,000 assays, 1,000 surface rock samples, 500 soil samples, as well as geophysics, Lidar and bedrock geology.

The area to be analyzed has numerous deposits including, but not limited to, Agnico Eagle's Upper Beaver, Kerr Addison, Mistango River Resources' Omega Mine and Gatling's 3 high-grade gold deposits: Fernland, Cheminis and Bear,Gatling said in a statement.

These known gold deposits will be instrumental in guiding the AI, with the goal of highlighting areas on Larder that may be geologically similar to other deposits in the district.

Contact the author: [emailprotected]

Follow him on Twitter @PatrickMGraham

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Gatling Exploration to use artificial intelligence to identify possible gold targets at the Larder project in Ontario - Proactive Investors USA &...

QAnon accounts banned by Twitter have already returned, with over 100,000 followers – The Daily Dot

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Last week, Twitter announced that after over two years of almost unchecked growth by the QAnon conspiracy theory, it was taking steps to crack down on the activity of believers, including targeted harassment and sharing of links to QAnon websites.

The effectiveness of that measure, however, is questionable. Major promoters, supposedly banned, are still rampantly posting.

QAnon, which holds that a military intelligence team is using the message board 8kun to leak clues to their upcoming (and forever delayed) purge of deep state sex traffickers, has grown explosively on Twitter since late 2017.

Twitter has outsized importance in the Q movement, as popular QAnon promoters use it to decode Qs posts, share videos and memes, alert Q acolytes to possible deep state comms hidden in tweets, and attempt to win over new converts.

From March to June 2020, there were over 12 million tweets that mentioned Q or one of its associated catchphrases, according to a new report from extremism research think tank the Institute for Strategic Dialogue.

Many of these tweets are also part of direct harassment swarms carried out against high-profile users who have fallen afoul of the Q movement, including Chrissy Teigen, Lady Gaga, Patton Oswalt, and Tom Hanks. And since the onset of the coronavirus pandemic, Twitter has seen a massive spike in QAnon disinformation and harassment, driven by the unchecked spread of coronavirus conspiracy theory videos like Plandemic. And just weeks earlier, Twitter was part of an explosive, QAnon-driven conspiracy theory that furniture giant Wayfair was using its website to sell missing children to traffickers.

So the site taking steps to curb the conspiracy theorys reach was greeted as positive news by journalists and Twitter users alike, even if Q fans rolled it into their conspiracy theory that the site was hopelessly under the sway of deep state-linked celebrities.

Twitter initially announced it would suspend 7,000 Q-related accounts responsible for abuse or ban evasion, stop recommending QAnon accounts in searches, suppress QAnon-friendly hashtags in trending topics, and prevent links to QAnon sites from being shared.

A week later, Twitter has indeed taken some of these steps. Some high-profile Q accounts have been banned, and its no longer possible to send direct messages with links to Q sites.

Overall, mentions of QAnon and its related hashtags are down across the board.

From July 15th to the 22nd there were one million QAnon posts from 427,000 unique authors, extremism researcher and Ph.D. candidate Marc-Andr Argentino told the Daily Dot. From the 22nd to the 28th there have been 809,000 posts, down 34 percent, from 302,000 unique authors, a number down 14 percent from just before the ban.

But a large-scale crackdown of QAnon believers and total suppression of the conspiracy theory either hasnt happened yet, or never was going to. Twitter never said it would entirely deplatform Q, the way Reddit did in 2018 when it banned dozens of Q subreddits. It would merely reduce the ability of users to find material related to the conspiracy and to limit its public reach.

More than that, almost all of the major banned accounts have already come back to the site with a new or alternate account and picked up right where they left off.

Within a few days of the news breaking, Twitter suspended several high-profile QAnon-promoting accounts. The first to go was Inevitable ET, an influential user with over a quarter of a million followers that had been banned well over a dozen times, only to create a new account each time.

A few days later, Twitter banned QAnon promoter and podcaster Tommy Tommy G. Gelati, after he had unleashed a swarm of harassment on Daily Beast writer Will Sommer, who had written a story about Gelatis previous conviction for bank robbery. Then on Monday, Twitter once again suspended QAnon promoter and conspiracy theorist Joe M, who had rebuilt his following under the name @SheepKnowMore after previously being banned in April as @StormIsUponUs.

These three QAnon promoters, with well over half-a-million followers total, were notorious for spreading conspiracy theories, harassment, and disinformation, as well as for creating new accounts to get around bans. They are just the sort of accounts tailormade for Twitter to ban as part of a sweeping crackdown on a violent conspiracy theory thats gotten out of control and made the site less safe for regular users.

But as of July 30, all three were already back on Twitter under newly created or reactivated alternate accounts: Joe M as @ToddBurgun, Tommy Gelati as @ReturnOfTheGedi and Inevitable ET as @mrbotus_520.

None of the three made any real effort to hide who they were, dropping easily deciphered clues into tweets on their new accounts or on Parler, where Q promoters tend to go to complain about their Twitter bans. They let Q fans know what new account to check out and instantly picked up tens of thousands of followers.

Together, they have racked up over 100,000 followers already, swiftly encroaching on their pre-ban reach.

Beyond allowing banned accounts to sneak back on, many other high-profile QAnon promoters are still active and prolifically spreading conspiracy theories. QAnon-driven disinformation is still going viral, including a recent video of a group of pro-hydroxychloroquine doctors that got millions of views in hours, thanks in part to being shared by Q promoters.

And Q believers are using alternate hashtags to get the word out, including #CueAnon and #17Anon, while regular favorites like #WWG1WGA are still easily searchable.

Twitter is by far the most important digital battlefield in the war that Q followers see themselves fighting against the deep state. Q believers wont give up on Twitter and migrate to a free speech site like Parler for this simple reason: Twitter is too popular with normie and awake users alike to walk away from.

So unless Twitter implements a real ban, QAnon is here to stay.

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QAnon accounts banned by Twitter have already returned, with over 100,000 followers - The Daily Dot

Insights & Outcomes: a new spin on quantum research, and the biology of sex – Yale News

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This month, Insights & Outcomes will turn your head with spinning electrons, prolific plankton, and the biology of sex.

As always, you can find more science and medicine research news onYaleNews Science & TechnologyandHealth & Medicinepages.

The group of single-celled marine organisms known as planktic foraminifera are among the most prolific shell producers in the open ocean. They leave behind one of the most extensive fossil records on the planet, and they allow scientists to reconstruct Earths climate history. Yet little was known about their life history until now. A research team led by Yale paleontologistCatherine Davisgrew a generation of planktic foraminifera in the lab and documented the organisms full life cycle. The team confirmed the organisms apparent ability to reproduce both sexually and asexually, and found that the shells of cloned siblings grown together in the laboratory can look strikingly different from each other. These results have broad impacts on how foraminifera fit into food webs, how vanishingly small populations can rapidly respond to their environment, and perhaps even their long-lived success as a group, said Davis, a postdoctoral associate in the lab ofPincelli Hull, assistant professor in the Department of Earth and Planetary Sciences and co-author of the study.The study appears in Science Advances.

Since 2003, the lab of YalesMark Gersteinhas played a major role in an international effort to catalog data on the complex interactions between genes and the segments of DNA and RNA that regulate their functions. The latest findings of the ENCODE project were published July 29 in 30 papers, four spearheaded by Gersteins lab, in a variety of scientific journals.Jing ZhangandDonghoon Leefrom Gersteins lab have createda video illustrating sciences evolving understandingof the complex regulatory networks that can contribute to cancer and other diseases.The latest findings by the Gerstein lab and other major ENCODE contributors can be found on the Gerstein lab website.

YalesNina Stachenfeldbelieves that to understand disease, scientists must understand the biology of sex. So she is helping to launch a series of papers for publication in The FASEB Journal that explores the systemic role sex plays in human physiology. Stachenfeld, a fellow at the John B. Pierce Laboratory and professor of obstetrics, gynecology, and reproductive sciences, has enlisted contributions from half a dozen scientists to explore a variety of topics, including the role sex plays in addiction and the biology of high blood pressure in people of different races. The series,Sex as a Variable in Human Research: A Systems Approach,will appear over the next few months in The FASEB Journal.

A research result by Yale physicists lends credibility to an exotic proposal for safeguarding quantum information called topological quantum protection. Topological quantum protection is an alternative to Yales primary approach to fault tolerant quantum computing based on active error correction. Rather, it involves a theoretically proposed entity called a Majorana quasiparticle, which has not yet been directly observed. A team led byMichel Devoret, the F.W. Beinecke Professor of Applied Physics and Physics, has applied the tools of circuit quantum electrodynamics to achieve the continuous monitoring of a quasiparticles spin, a promising step toward detection of Majorana quasiparticles. The Yale team includesMax Hays,Valla Fatemi,Kyle Serniak, andSpencer Diamond. Thestudy appears in Nature Physics.

When pathogens or cancer cells develop resistance to drug treatment, researchers usually try to develop new drugs. But a new study by Yale researchers helps bolster a new strategy taking advantage of evolutionary processes to combat drug resistance through drug-sensitive pathogenic cells. The new approach, known as adaptive therapy, offers an alternative to prolonged and high-dose drug treatment for cancer or infections. Adaptive therapy calls for an intermittent series of lower dose treatments that kill fewer disease-causing cells but also decrease the chances that those cells develop resistance to the drugs. In other words, as long as a pathogen or cancer remains responsive to a drug, it may be wiser, in some instances, to manage a disease rather than trying to eradicate it at the expense of an elevated risk of drug resistance evolution, saidSergey Melnikov, lead author of the new study. It is based on his work in the lab of YalesDieter Soll, Sterling Professor of Molecular Biophysics and Biochemistry and professor of chemistry. In a laboratory experiment, Melnikov and Soll gave adaptive therapy a boost by adding the amino acid norvaline to the antibiotic tavaborole to combat drug-resistant E. coli. Norvaline impairs the ability of E. coli cells to produce cells resistant to tavaborole by hindering their ability to mutate, allowing antibiotic-sensitive cells to outcompete antibiotic-resistant ones. By integrating Darwinian principles of natural selection into therapeutic treatment of a disease,we can significantly prolong the effectiveness of drugs or give a second life for drugs that are currently abandoned due to rapid evolution of resistance, said Melnikov, now a group leader at Newcastle University.The study was published in the Proceedings of the National Academy of Sciences.

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Machine Learning And Organizational Change At Southern California Edison – Forbes

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An electrical lineman for Southern California Edison works on replacing a transformer as a whole ... [+] block is rewired. Long Beach, California. April 2014.

Analytics are typically viewed as an exercise in data, software and hardware. However, if the analytics are intended to influence decisions and actions, they are also an exercise in organizational change. Companies that dont view them as such are likely not to get much value from their analytics projects.

One organization that is pursuing analytics-based organizational change is Southern California Edison (SCE). One key focus of their activity is safety predictive analyticsunderstanding and predicting high risk work activities by the companys field employees that might lead to a life threatening and/or life altering incident causing injury or death. Safety issues, as you might expect, are fraught with organizational perilpolitics, lack of transparency, labor relations, and so forth. Even reporting a close call runs counter to typical organizational cultures. These organizational perils are a concern to SCE as well, but the company has created an approach to address them. SCE hasnt completely mastered safety predictive analytics and the requisite organizational changes, but its making great progress.

A Structure for Producing Analytical Change

Key to the success of the SCE approach is the structure of the analytical team that is addressing safety analytics. It is small, experienced, and integrated. Two of the key members of the team are Jeff Moore and Rosemary Perez, and they make a dynamic combination. Moore is a data scientist who works in the IT function; Perez works in Safety, Security, and Business Resiliency, and is a Predictive Analytics Advisor. In effect, Moore handles all the analytics and modeling activities on the project, and Perez, who has many years of experience in the field at SCE, leads the change management activities.

Steps to manage organizational change started at the beginning of the project and have persisted throughout it. One of the first objectives was to explain the model and variable insights to management. Outlining the range of possible outcomes allowed Perez and Moore to gain the support needed for a company wide deployment. Since Perez had relationships and trust in the districts, she could introduce the project concept to field management and staff without the concern about Why is Corporate here?. Perez noted that its important to be transparent when speaking with the teams. That trust has resulted in the district staffs willingness to listen and share their ideas on how best to deploy the model, to address missing variables and data, and to drive higher levels of adoption.

The team took all the time needed to get stakeholders engaged. Moore came into the project in the summer of 2018, and he was able to get a machine learning model up and running in a month or so, but presenting it, socializing it, and gaining buy-in for it took far longer. Moore and Perez met with executives of SCE in November and December of 2018. Within days of these meetings the safety model analytics project became a 2019 corporate goal for SCE. Safety was the companys number one priority, and it was willing to try innovative ideas to move it forward. For such a small team to have their work made into a corporate goal is unusual at SCE and elsewhere.

The Risk Model and its Findings

SCE now has an analytical risk-based framework, and risk scores for specific types of work activities and the context of the work. The model draws from a large data warehouse at SCE with work order data, structure characteristics, injury records, experience and training, and planning detail. All those factors were not previously linked, and there wasas is often the case with analyticsconsiderable data engineering necessary to pull together and relate the data.

The machine learning model scores activities that teams in the field perform, like setting a new pole or replacing an insulator. Each activity may be more or less dangerous depending on the time of year, day of the week, weather, crew size and composition, and so forth. Replacing a pole, for example, may be only a moderate risk task in itself, but when done on the side of a hill in the rain with a crane it becomes very high risk. Instead of generic safety messages to employees, SCE can now get much more specific by describing the risk of particular activities they perform on the job in a particular context.

As the model learns it will recommend specific approaches to reduce the risk of a job, like altering the crew mix or crew size, requiring additional management presence, using specific equipment or rigging to perform the work, or creating a longer power outage in order to do the job more slowly. The latter recommendation runs counter to the culture of not inconveniencing customers, but if the model specifically recommends it, then the teams will discuss the contributing factors as well as their years of experience to mitigate the risk before executing the work.

The project has led to several more general findings, which are of greatest interest to SCE executives. For example, management has long been interested in using data to understand changing safety risk profiles of the field teams over time as a result of increasing/decreasing workloads or as weather patterns change. While the predictive model considers more than 200 variables, the findings from the model have been summarized into the top fifteen distinct drivers of serious injury and fatality. Some shifting of variables is expected over time, but there has been great interest in better understanding the initial set of risk factors.

Deploying the Model and Needed Organizational Changes

Moore and Perez are in the early stages of deploying the model; theyve rolled it out to six of 35 districts thus far. Each district has a unique personality, and they dont want cookie-cutter answers on how to deploy in their district.

Moore, whose primary role was to create the model, said he has realized that safety analytics are not just about a model. I started out thinking it was about an algorithm, but I realized many other factors were involved in improving safety. Moore said that he gets some pressure to move on to analytics in other parts of the business, but in order to see your models come to life you have to go through this kind of process. And everyone at SCE believes the safety work is critical.

Perez, whose primary focus is change management, listed some of the organizational changes in deployment. There might be training issuesnot only on analytics, but also communication, leadership and ownership. There might be process concernshow we plan and communicate work. There may be technology concerns in using the system.

Perez also says the process of working with a district is critical. You cant just walk into a district and disrupt their work flow for no reason, she says. They want to know your purpose and your objective. We try to connect, show transparency, and build trust that we are here to help, that we are here to observe how they mitigate risk, to share our findings, and to see how the findings might be integrated into their work practices. We hope they will help us understand the complexity they face every day.

Both team members say they learn something every time they visit a district. Moore notes, You can only see the data you can see in the data warehousetime sheets, work orders, etc. But when you talk to the people who do the work, you learn a lot about how the data is created and applied. With each visit I understand the drivers better and the complexity of the work. I can also speak the language better with each district visit, and I understand the process and the equipment better as well.

With the findings from the model, Moore and Perez are beginning to work with another partner at SCEthe HR organization. It is responsible for defining work practices, training needs, standard operating procedures, and job aids. Each of these is potentially influenced by findings about safety risks, so the goal is to incorporate analytical results into the practices and procedures.

The team is already working to modify the model to incorporate new factorsone of which, not surprisingly given the situation in California, involves the risk of wildfires. Moore and Perez are also trying to create more integration of the risk scores with the work order system. They also plan to try to incorporate the risk model into other SCE business functions like Engineering, which might be able to lower the risk in the planning and construction of the electric grid. All in all, using data and analytics to improve safety is a time-consuming and multifaceted process, but what could be more important than reducing injury and fatality among SCE employees and work crews?

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Machine Learning And Organizational Change At Southern California Edison - Forbes

97 Things About Ethics Everyone In Data Science Should Know – Machine Learning Times – machine learning & data science news – The Predictive…

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Every now and then an opportunity comes along that you just cant pass up. One such opportunity that fell into my lap was when OReilly media reached out to me to see if I was interested in partnering on a collaborative book on the ethics that surround data science. For those who know me and follow my work, they have seen me calling for more focus on ethics for several years. Ive written blogs and papers on the topic, Ive given many conference presentations on the topic (including at Predictive Analytics World 2019!), and Ive had countless discussions with clients

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National Whistleblower Appreciation Day And Its Many Contradictions – Shadowproof

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Editors Note Substack is dealing with a bad bug that has interfered with our ability to bring on new paid subscribers for over a week. This is unfortunate, as it has undermined the launch of The Dissenter newsletter. Until Substack can fix this, all editions, including exclusive editions, will be sent to everyone.

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On July 30, 2013, United States Army whistleblower Chelsea Manning was convicted of violating the Espionage Act and various other offenses.

It was National Whistleblower Appreciation Day, and though she was not found guilty of aiding the enemy, the verdict in her trial crystallized a contradiction among the political establishment. Officials profess a commitment to whistleblowers except when they blow the whistle on abuse, fraud, or corruption that they have a vested interest in defending.

The resolution for this years National Whistleblower Appreciation Day, like prior resolutions, stipulates that the United States will encourage whistleblowing but only according to federal law and only if it protects classified information (including sources and methods of detection of classified information) and also only if the whistleblowing involves honest and good faith reporting of misconduct, fraud, misdemeanors, and other crimes to the appropriate authority at the earliest time possible.

With those disqualifiers, Manning, NSA whistleblower Edward Snowden, FBI whistleblower Terry Albury, NSA whistleblower Reality Winner, alleged drone whistleblower Daniel Hale, and a number of other whistleblowers in recent history are rendered criminals.

Both Albury and Winner pled guilty to violating the Espionage Act and were sentenced to federal prison, where they are at the mercy of the Bureau of Prisons (BOP) cold-hearted protocols during the COVID-19 pandemic.

Hale was charged with violating the Espionage Act, but the pandemic delayed his trial.

Snowden remains in Russia, where he has lived for around seven years under political asylum. He was charged with violating the Espionage Act and trapped in the country after the State Department revoked his passport. (The Justice Department is now criminalizing WikiLeaks founder Julian Assange and other WikiLeaks staff for engaging in source protection and helping Snowden travel from Hong Kong.)

Republican Senator Chuck Grassley and other U.S. senators, who support National Whistleblower Appreciation Day, do not view these whistleblowers as the whistleblowers they are. They did not blow the whistle the right way. They did not prioritize the interests of the national security state or military industrial-complex. That makes them insider threats, or worse, traitors.

There are whistleblowers from the Organization for the Prohibition of Chemical Weapons (OPCW), who have exposed lies and disinformation around the case for military strike against Syria. Unfortunately, neither Democrats nor Republicans care much for what they have exposed to the world.

Who is and is not a whistleblower has grown more partisan. Under President Donald Trump, Democrats have their whistleblowers, who Republicans refuse to recognize. Likewise, when Barack Obama was president, Republicans had their own individuals who they designated as whistleblowers, which Democrats treated as illegitimate (Larry Alt and Pete Forcelli, who exposed the Operation Fast and Furious scandal, are good examples).

Support for whistleblowers may always be fraught with contradictions and inconsistencies within institutions and among political elites. Yet, the global COVID-19 pandemic and its impact on low-income, working class, and middle class Americans has shown how crucial it is to protect whistleblowers.

Countless citizens have risked their careers and jobs during a time when unemployment has skyrocketed and millions have been stripped of their health insurance.

A slaughterhouse worker in Denver blew the whistle on unsafe working conditions. Medical center staff in California revealed that management kept them in the dark as COVID-19 spread among nurses.

Prison staff at Federal Medical Center Carswell in Fort Worth, Texas, complained in April that the BOP was knowingly misleading the public on the threat of COVID-19 to prisoners and staff. Months later, Carswell had a massive outbreak where around 40 percent of prisoners tested positive for COVID-19.

Lauri Mazurkiewicz was fired from her job as a nurse at Northwestern Memorial Hospital in Chicago after she emailed colleagues that she did not want to work without a mask. She has asthma and an elderly father with a respiratory disease.

Corporate retaliation against whistleblowers was documented throughout the country. At an Amazon warehouse in Staten Island, New York, Chris Smalls was fired after he brought attention to Amazons lack of concern for worker safety. But what Smalls and others revealed was largely validated, and it sparked an investigation by the New York Attorney Generals office that forced Amazon to make modest changes to workplace conditions.

In recent weeks, media reports have brought attention to a blacklist that McDonalds management apparently has at some franchise locations, where mitoteros, which translates into gossipers or troublemakers, are designated for termination, especially if they organize workers for better conditions.

The Occupational and Safety Health Administration (OSHA), which is part of the Labor Department, was reportedly receiving two dozen whistleblower complaints a day during the COVID-19 pandemic. OSHA had over 1,000 open complaints in May. However, when Grassley and others celebrate whistleblowers, these are not the kind of whistleblowers they support because they make it harder for corporations that fund their campaigns to continuously make record profits.

Days for celebrating whistleblowers are certainly important, and there are plenty of lesser known whistleblowers, who this newsletter will spotlight. But as necessary is a shift in the culture away from one that lets officials arbitrarily decide who is and is not a whistleblower and which dissenters citizens are allowed to support.

Our advocacy must not limit whistleblowing to proper channels that are compromised or terribly constrained by authorities that will see to it that they do not work.

To truly appreciate whistleblowers, we need to see the press and public as one of the proper channels for revealing corruption and create greater protections for freedom of speech and expression that shield employees in corporations and governments from termination and prosecution.

***

Note: The July 30 edition of Dissenter Weekly will air at 1:45 PM ET and feature CIA whistleblower John Kiriakou. Well be spotlighting some lesser known whistleblowers who deserve celebration. You can watch a livestream on our Youtube.

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National Whistleblower Appreciation Day And Its Many Contradictions - Shadowproof

Australia urged to invest in quantum computing ahead of future pandemics – Sydney Morning Herald

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Quantum approaches could play a significant role in developing treatments for any future pandemics more efficiently, improving the calculations that have to be made in chemical research and helping bringing new treatments to market.

"Advances in computing tech have given enormous practical advances in medicine and we think quantum has a role in drug discoveries," Professor Biercuk said.

These types of technologies are incredibly fragile, however, and Q-CTRL is in the business of offering technology solutions to industry that help stabilise quantum computing processes.

The company, which was spun out of the University of Sydney, has been backed by leading local venture capital firms including Square Peg, which led a $22 million funding round in the business last year.

The CSIRO released a road map for quantum computing investment this year, though much of the research and development work being done in the sector is occurring offshore.

"There is not very much in the Australian market at this time... we are almost 100 per cent export-focused in our company," Professor Biercuk said.

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Over recent months, industry experts right across the technology sector have been championing the importance of targeting investment in research and development projects that could help Australia face future pandemics better and export skills in a post-COVID economy. This includes expanding vaccine manufacturing facilities and ensuring research and development incentives support the biotech industry.

A report on COVID-19 from the Medical Technology Association of Australia said industry should be brought to the table to work with governments on any future pandemic planning.

"Any new or updated national pandemic preparedness plan must recognise the critical role of the medtech industry," the report said.

Federal and state governments have contributed to a range of quantum computing projects over the past five years as researchers race to make quantum computers a reality.

The path could take hundreds of millions of dollars and many years, Professor Biercuk said, much like the pharmaceutical sector needs long-term investors to survive.

"The investment needed is actually similar to that for drug development. It means the investors we have attracted have a very long-term approach to this."

Emma is the small business reporter for The Age and Sydney Morning Herald based in Melbourne.

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Australia urged to invest in quantum computing ahead of future pandemics - Sydney Morning Herald

IBM, University of Tokyo Launch the Quantum Innovation Initiative Consortium – HPCwire

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TOKYO,July 30, 2020 IBM and theUniversity of Tokyounveiled a landmark collaboration with the launch of the Quantum Innovation Initiative Consortium (QIIC). Expanding from theDecember 2019JapanIBM Quantum Partnership initiative, QIIC, aims to accelerate the collaboration between industry, academia, and government to advanceJapansleadership in quantum science, business, and education.

QIICs main goal is to strategically accelerate quantum computing R&D activities inJapanby bringing together academic talent from across the countrys universities and prominent research associations and large-scale industry. The consortium plans to further develop technology for quantum computing inJapanand build an ecosystem to improve student skills and expertise, opening doors to future scientific discoveries and practical quantum applications.

Headquartered at theUniversity of Tokyo, member organizations of QIIC will collaborate to engage students, faculty, and industry researchers with seminars, workshops, and events to foster new quantum business opportunities inJapan. Organizations in agreement to join the consortiumincludeKeio University, Toshiba, Hitachi, Mizuho,MUFG, JSR, DIC, Toyota, Mitsubishi Chemicals and IBM Japan.

These organizations in consortium will also be part of the IBM Q Network the worlds first community of Fortune 500 companies, startups, academic institutions and research labs to advance quantum computing and the development of practical applications for it. As part of the network, they will have access to IBMs expertise and resources, and cloud development environment, as well as cloud-based access to the IBM Quantum Computation Center, which includes IBMs most-advanced quantum computers.

In addition to cloud-based access to the IBMs fleet of quantum systems, the QIIC will also have access to an IBM Q System One, a dedicated system planned for installation inJapanin 2021. The first of its kind in the region, and only the second such installation outside of the US, this system along with a separate testbed system to be part of a system technology development lab will support the consortiums goals of next-generation quantum hardware research and development, including cryogenic components, room temperature electronics, and micro-signal generators.

According to ProfessorMakoto Gonokami, President of theUniversity of Tokyo:

Society 5.0is the concept of a better future with inclusive, sustainable and a knowledge-intensive society where information and services create value underpinned by digital innovation. The key to realizing this society is to utilize real data in real-time. In order to achieve this, it is necessary to protect and nurture the global environment, an entity of physical space and cyberspace as one, by taking it as a global commons (a concept that encompasses global resources and the ecosystems) which is sustainable and reliable, while the fusion of physical space and cyberspace progresses.

Quantum technology and quantum computers are indispensable technologies to make that happen. I believe thatJapanwill play an important role in implementing quantum computing technology to society ahead of rest of the world, and that industry-academia-government collaboration is necessary for this. The QIIC will accelerate quantum technology research and its implementation to the Society 5.0 while firmlysharing each others wisdom and promoting the close sharing of information.

Today, I am extremely excited and proud to launch this new consortium that will help foster economic growth and quantum technology leadership in Japan.The QIIC will greatly advanceJapansentire quantum computing ecosystem, bringing experts from industry, government and academia together to collaborate on researchand development, saidDario Gil, Director of IBM Research. Quantum computing has the potential totackle some of the worlds greatest challengesin the future.We expect that it will helpusaccelerate scientific discovery so that we candevelop vaccinesmore quickly and accurately,create new materials toaddressclimate changeor design better energy storage technologies. The potential is massive,andwe will only reach this future if we work together uniting the best minds from the public and private sectors. Universities, businesses and governments have to collaborate so that we can unleash the full potential of quantum computing.

QIICs members are forging a path forJapansdiscovery of practical quantum applications for the benefit of society. The cooperation between industry, academia, and government aims to create a new community for quantum computation research and use cases.

About IBM Quantum

IBM Quantum is an industry-first initiative to build quantum systems for business and science applications. For more information about IBMs quantum computing efforts, please visitwww.ibm.com/ibmq.

For more information about the IBM Q Network, as well as a full list of all partners, members, and hubs, visithttps://www.research.ibm.com/ibm-q/network/

About TheUniversity of Tokyo

TheUniversity of Tokyowas established in 1877 as the first national university inJapan. As a leading research university, theUniversity of Tokyois conducting academic research in almost all fields at both undergraduate and graduate schools. The University aims to provide its students with a rich and varied academic environment that ensures opportunities for acquiring both academic and professional knowledge and skills.

Source: IBM

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IBM, University of Tokyo Launch the Quantum Innovation Initiative Consortium - HPCwire


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