If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Listen to this episode from Tcast on Spotify. Artificial Intelligence is all the rage these days. There are universities doing research, op-eds in newspapers, and even several articles in this space talking about artificial intelligence and machine learning and how it will affect our lives in the years to come. Unfortunately, most of the focus has been on how it can be used to improve the bottom lines for businesses around the world. Don’t get us wrong, we’re not knocking the profit motive. However, we are knocking the idea that you have to keep on making more and more profit. That drive has a way of dehumanizing people (and frankly even the people with the drive) and making people lose focus on the things that really matter in the world. One of the effects of the constant drive for more profits is the drive to consume more things. More and more we look like Huxley’s Brave New World in which consumerism is promoted by the state, to the extent they put out slogans like “the less stitches, the more riches” to promote people buying new clothes instead of mending what they already have. Every economic ‘stimulus’ is given in the hopes that people use that money to go buy a bunch of stuff to keep things moving. Consumerism is a huge problem in the modern world. This is true both spiritually and materially, though for this article we’ll be focused on the material problems. Whether it is the government or business telling us that the way to happiness is the latest and greatest smartphone, TV, car, etc. this creates problems. All of that stuff requires resources to make. Minerals, trees, oils and who knows what are used every time something like that is purchased. And the old goes into landfills, which are gigantic, so gigantic in some places that people literally live on them in places like India, making a living off reselling some of the things in them. We’ve gotten better at reusing a lot of that stuff, being able to recycle things made of the rare minerals mined in Africa or melting down plastics so they can be remolded into something else. However, there is a finite amount of stuff on the planet and a growing population that will naturally keep using that stuff. We might well find ourselves able to get into space and use resources there before much longer, but it wouldn’t hurt to also reduce our dependency on the drive to constantly have more stuff as well. Which brings us back to our primary issue for this article, how can we use our digital technology to reduce that need? How can we use things like AI to make things more sustainable? Fortunately, our ability to collect and analyze data is just as unparalleled as our increased drive to consumerism. Improved analytics can be used for a variety of efforts that will make farming more efficient, enabling people to get the most food out of a plot of land while doing the least amount of harm to the environment. We can learn how to build safer, smaller, and lighter vehicles so that they use fewer resources, are more fuel efficient and still allow people to get from point A to point B. AI can be used to study the effects of different zoning laws. Would it be better to allow more mixing of business and residential areas so people don’t need to drive ten minutes whenever they need a gallon of milk? There is a lot of potential here. And a lot of ways that potential can be undermined. We’ll be exploring both of those a bit more next time. What’s your data worth? www.tartle.co
TL;DR: The 2021 Ultimate Adobe Designers Bundle is on sale for £32.16 as of June 19, saving you 98% on list price. Graphic design is a useful skill set that can help any business owner, podcaster, or even influencer enhance their own brand. If you want to boost your digital artistry and create better designs, logos, and more, the 2021 Ultimate Adobe Design Bundle is an easy way to build your skills. This 12-course bundle features over 500 lessons that you can tune into and absorb at your own pace -- once you gain access to them, you'll have access for life. First, you'll take the digital productivity course, which includes a digital journal to track daily habits, to-do lists, and more.
In honor of Juneteenth, Google Assistant has an important new feature. "Hey Google, what happened today in Black history? On Saturday morning, Google unveiled the addition of a Black history function, available to users of any Assistant-enabled smart speaker, smart display, or phone. Just ask "Hey Google, what happened today in Black history?" and the voice assistant will recite daily history content curated by Google with the help of civil rights activist and scholar Dr. Carl Mack. The facts are intended to highlight important Black cultural events and leaders as the United States continues its racial reckoning. The feature is one of numerous initiatives being taken not just by Google, but also countless other companies as many of them honor Juneteenth for the first time. On Wednesday, President Biden officially made the day, which commemorates the emancipation of enslaved people, a federal holiday, recognized in all 50 states. You can read more about Juneteenth here. At Google, the company also released a new Doodle from Detroit-based artist Rachelle Baker, honoring Black joy and artistic contributions. In a Google press release sent to Mashable, Baker described her process creating the Doodle, saying, "I looked at tons of photos and art illustrating some of the first ever Juneteenth celebration, as well as celebrations, parades, and festivities from recent years.
At Kinaxis, who we are is grounded in our common belief that people matter. Each one of us plays an important part in accomplishing our work, building our culture and making a global impact. Every day, we're empowered to work together to help our customers make fast, confident planning decisions. This is how we create a better planet – for each other, for our customers and for generations to come. Our cloud-based platform RapidResponse ensures that the products we need – everything from medicine and cars, to day-to-day items like toothpaste – make it to market and into our hands when we need them with minimal ecological footprint.
AI budgets are up significantly over the past year as companies compete to survive and grow market share during the global pandemic, according to Appen, which published its State of AI and Machine Learning report this week. The study also detected a correlation between AI budget size and the likelihood that AI projects will actually be deployed on the one hand, and budgets and the use of external data providers on the other. Now in its seventh year, Appen's State of AI seeks to generate a broad snapshot of AI investments across the United States. The company contracted with Harris Poll to investigate various aspects of AI investments and project management at 500 companies, all of which had at least 100 employees. The growth in AI budgets was perhaps the most compelling result to come out of the study, which had a margin of error of 5%. According to the study, the number of companies with budgets ranging from $500k to $5 million increased by 55% compared to last year.
Argo AI is in the business of building self-driving technology you can trust. With experienced leaders in the field and collaborative partnerships with some of the world's largest automakers, we're building self-driving technology that is engineered to scale globally and transform mobility for millions. Talented individuals join our team because they share our purpose to make it safe, easy, and enjoyable for everyone to get around cities. We aspire to impact key industries that move people and goods, from ride hailing to deliveries. Our team delivers solutions to camera-based perception problems on the autonomous vehicle platform. These problems include object detection, scene segmentation, and various classification and regression problems.
Xilinx has introduced its Kria programmable chips and boards for holding AI applications at the edge of the network. This should come in handy for visual applications like smarter cameras. San Jose, California-based Xilinx, which is in the process of being acquired by Advanced Micro Devices (AMD) for $35 billion, has a group of products dubbed the Kria portfolio of adaptive system-on-module offerings for AI at the edge. These are production-ready small form factor embedded boards that enable rapid deployment in edge-based applications. Coupled with a complete software stack and prebuilt, production-grade accelerated applications, Kria adaptive modules are a new method of bringing adaptive computing to AI and software developers.
For lung nodules, CNN have been shown to distinguish between benign and malignant classifications at a higher performance than traditional CADx systems due to their ability to function at higher degrees of noise tolerance (Hosny et al. 2018; Nasrullah et al. 2019). Furthermore, in a study done on patients with non-small cell lung cancer, AI CADx algorithms were able to use CT images to significantly predict which cancers contained EGFR mutations, informing on potential treatment with Gefitinib (Bi et al. 2019). Deep learning algorithms have also been trained to accurately classify prostate cancer on Magnetic Resonance Imaging (MRI), which can promote early treatment as well as decrease the number of unnecessary prostate biopsies and prostatectomy procedures performed (Bi et al. 2019). An additional study reported an AI system that was able to use MRI imaging to accurately generate brain tumour classification differentials at a level that exceeded human performance. The algorithm generated the correct diagnosis in one of its top three differentials 91% of the time, outperforming academic neuroradiologists (86%), fellows (77%), general radiologists (57%), and radiology residents (56%) (Rauschecker et al. 2020).
Analytics India Magazine got in touch with Abhishek Bhandwaldar, Research Engineer at IBM to understand his machine learning journey. Abhishek has a Master's in Computer Science from the University of North Carolina. "It is important to have a basic understanding of the different topics in the field to make sure you end up in the area you feel most passionate about," says Abhishek. Abhishek: My introduction to AI was through video games. Then, I read about how'Deep Blue' devised long-term strategies and beat an expert opponent in chess.
Have you been in a situation where you expected your machine learning model to perform really well but it sputtered out a poor accuracy? You've done all the hard work – so where did the classification model go wrong? How can you correct this? There are plenty of ways to gauge the performance of your classification model but none have stood the test of time like the confusion matrix. It helps us evaluate how our model performed, where it went wrong and offers us guidance to correct our path.