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Apollo Tyres Goes All-In on AWS to Make Factories Smarter with IoT and Machine Learning - ELE Times

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Amazon Web Services (AWS) announced that Apollo Tyres, India's leading tyre manufacturer, is going all-in on AWS to digitally transform. By moving all of its IT infrastructures to AWS, Apollo Tyres can use AWS's broad portfolio of services to innovate new customer experiences while driving productivity, compliance, and process efficiency gains globally, across seven factories. Apollo Tyres will draw on the breadth and depth of AWS capabilities, including Internet of Things (IoT), data and analytics, and machine learning, to transform into an agile, data-driven enterprise. Using data from the factory floor and real-time information from production machines, like tyre rubber mixer machines, Apollo Tyres can expand operational intelligence capabilities and more accurately manage machine utilisation, ensuring high-quality levels and machine efficiency. With AWS, Apollo Tyres is connecting all of its factories in the cloud this year in India and Europe.


@Radiology_AI

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To determine whether deep learning algorithms developed in a public competition could identify lung cancer on low-dose CT scans with a performance similar to that of radiologists. In this retrospective study, a dataset consisting of 300 patient scans was used for model assessment; 150 patient scans were from the competition set and 150 were from an independent dataset. Both test datasets contained 50 cancer-positive scans and 100 cancer-negative scans. The reference standard was set by histopathologic examination for cancer-positive scans and imaging follow-up for at least 2 years for cancer-negative scans. The test datasets were applied to the three top-performing algorithms from the Kaggle Data Science Bowl 2017 public competition: grt123, Julian de Wit and Daniel Hammack (JWDH), and Aidence.


US and China Race to Control the Future Through Artificial Intelligence

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As every aspect of modern life becomes more and more digitized, not just the economies of nations, but their sovereign influence will rely more and more on their command of technology, and especially the emerging technology of artificial intelligence (AI). In the 21st-century information technology revolution, whoever reaches a breakthrough in developing AI will come to dominate the world. "Artificial intelligence is a resource of colossal power," Russian President Vladimir Putin said at AI Journey 2019 conference, a major Eastern European forum on AI held in Moscow on Nov. 9, 2019. "Those who will own it will take the lead and will acquire a huge competitive edge." Putin expressed his concern about Russia's role in the artificial intelligence race in the forum--its two competitors, the United States and China, are far ahead of other countries in the AI race. "We must, and I am confident that we can become one of the global leaders in AI. This is a matter of our future, of Russia's place in the world," Putin added. Though the United States is still the world leader in terms of AI, China is quickly moving to take its place. On Oct. 16, Nicolas Chaillan, the former chief software officer of the U.S. Air Force, told The Epoch Times that the United States is set to lose the AI race against communist China if Washington doesn't act fast.


Worried about AI ethics? Worry about developers' ethics first

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Artificial intelligence is already making decisions in the fields of business, health care and manufacturing. But AI algorithms generally still get help from people applying checks and making the final call. What would happen if AI systems had to make independent decisions, and ones that could mean life or death for humans? Pop culture has long portrayed our general distrust of AI. In the 2004 sci-fi movie I, Robot, detective Del Spooner (played by Will Smith) is suspicious of robots after being rescued by one from a car crash, while a 12-year-old girl was left to drown.


New Smithsonian exhibit features first 'genderless voice assistant'

FOX News

January Littlejohn's lawyer explained how the school treated her like she was a danger to her child on'Fox News Primetime.' A new exhibit at the Smithsonian Institution features an interactive display that incorporates the first "genderless voice assistant." The voice assistant, known as "Q," is located at the FUTURES exhibit and the Smithsonian's website describes it as a voice that "was synthesized by combining recordings of people who identify variously as male, female, transgender, or nonbinary." "By mixing multiple voices together, Q's makers have created a voice'for a future where we are no longer defined by gender, but rather by how we define ourselves,'" the website says. The genderless voice system was developed over the last few years by a Danish company called Virtue Nordic and it describes itself as "like Siri or Alexa but without the gender."


Eliminating AI Bias

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The primary purpose of Artificial Intelligence (AI) is to reduce manual labour by using a machine's ability to scan large amounts of data to detect underlying patterns and anomalies in order to save time and raise efficiency. However, AI algorithms are not immune to bias. As AI algorithms can have long-term impacts on an organisation's reputation and severe consequences for the public, it is important to ensure that they are not biased towards a particular subgroup within a population. In layman's terms, algorithmic bias within AI algorithms occurs when the outcome is a lack of fairness or a favouritism towards one group due to a specific categorical distinction, where the categories are ethnicity, age, gender, qualifications, disabilities, and geographic location. If this in-depth educational content is useful for you, subscribe to our AI research mailing list to be alerted when we release new material. AI Bias takes place when assumptions are made incorrectly about the dataset or the model output during the machine learning process, which subsequently leads to unfair results. Bias can occur during the design of the project or in the data collection process that produces output that unfairly represents the population. For example, a survey posted on Facebook asking about people's perceptions of the COVID-19 lockdown in Victoria finds that 90% of Victorians are afraid of travelling interstate and overseas due to the pandemic. This statement is flawed because it is based upon individuals that access social media (i.e., Facebook) only, could include users that are not located in Victoria, and may overrepresent a particular age group (i.e. To effectively identify AI Bias, we need to look for presence of bias across the AI Lifecycle shown in Figure 1.


Tesla Working on Full Self-Driving Mode, Extending AI Lead - AI Trends

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Tesla's goal to release its level 5 Full Self Driving (FSD) mode autopilot capability in 2021 was deemed unrealistic by the CEO of competitor Waymo in a recent interview. Tesla is the only autonomous vehicle manufacturer using real-time cameras, rather than pre-mapped Lidar (Light Detection and Ranging) to guide vehicle movement. Tesla also uses its own AI chips, developed after early experience with NVIDIA chips. "It is a misconception that you can simply develop a driver-assistance system further until one day you can magically jump to a fully autonomous driving system," stated John Krafcik, CEO of Waymo, the self-driving startup spun off from Google's X lab, in a recent interview with German business magazine Manager Magazin, reported in Observer. Krafcik acknowledged that Tesla "is developing a really good driver assistance system," but very different.


Role of choosing correct loss function

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Readers of this blog already know what loss functions are in AI but for people starting into the field let me define it again. The loss function is a mathematical equation that all the deep learning algorithm tries to minimize or optimize. As we all know that Deep learning takes an iterative process to learn things, in every step, it calculates some metric that tells it how close it is to the original label and based upon that it optimizes its parameters. So the metrics that we minimize or optimize are called loss functions. There are a lot of famous loss functions like Mean square error, categorical cross-entropy, Dice loss, and many more.


90Days Data Science Bootcamp: Build Portfolio Of 90 Projects

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We accelerate data science adoption for individuals, companies, and institutions through immersive bootcamps, workshops, corporate training, and corporate ... We'll Cover Everything You Need To Know For The Full Data Science And Machine Learning Tech Stack Required At The World's Top Companies. Our Students Have Gotten Jobs At Dell, Google Developers, Tcs, Wipro And Other Top Tech Companies! We've Structured The Course Using Our Experience Teaching Both Online And In-Person To Deliver A Clear And Structured Approach That Will Guide You Through Understanding Not Just How To Use Data Science And Machine Learning Libraries, But Why We Use Them. This Course Is Balanced Between Practical Real World Case Studies And Mathematical Theory Behind The Machine Learning Algorithms. How Much Does A Data Scientist Make In The United States?


Want to develop ethical AI? Then we need more African voices

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Artificial intelligence (AI) was once the stuff of science fiction. It is used in mobile phone technology and motor vehicles. But concerns have emerged about the accountability of AI and related technologies like machine learning. In December 2020 a computer scientist, Timnit Gebru, was fired from Google's Ethical AI team. She had previously raised the alarm about the social effects of bias in AI technologies.