on silicon makes no fundamental difference; we should each be treated with appropriate respect.” - Sir Arthur C. Clarke (16 December 1917 – 19 March 2008), 2010: Odyssey Two
people with disabilities through more intelligent technology? Daily Life How can AI increase access to technology for people with disabilities, while also decreasing the cost of such technology? Communication & Connection How can AI help improve the speed, accuracy, and convenience of communication for people with disabilities? AGE OF AI Ep3 - youtube.com/watch
they’re trying to write down three ideas and they can only speak (to their phone or smart home device), it will make sure all three ideas are jotted down. Smart Home Device Adoption Personal smart devices (Alexa, Google Home, etc), all of them are becoming the norm for people to interact with content. It’s incredibly powerful for people with disabilities. Interactive Voice-Powered Web pages Being able to interact with web pages via voice…there are technologies out there that kind of do it but we haven’t really seen the potential yet
every computing environment. To reduce our effort in typing most of the keyboards today give advanced prediction facilities. it predicts the next character, or next word or even it can autocomplete the entire sentence. Predictive Keyboards.
attributed to “fat finger typing” (or tracing spatially similar words in glide typing) along with cognitive and motor errors (manifesting in misspellings, character insertions, deletions or swaps, etc). An intelligent keyboard needs to be able to account for these errors and predict the intended words rapidly and accurately. As such, we built a spatial model for Gboard that addresses these errors at the character level, mapping the touch points on the screen to actual keys. The Machine Intelligence Behind Gboard https://ai.googleblog.com/2017/05/the-machine-intelligence-behind- gboard.html
by users who are visually impaired is identifying packaged foods, both in a grocery store and also in their kitchen cupboard at home. This is because many foods share the same packaging, such as boxes, tins, bottles and jars, and only differ in the text and imagery printed on the label. However, the ubiquity of smart mobile devices provides an opportunity to address such challenges using machine learning (ML).
new participants, which resulted in 864 gesture samples (12 participants performed eight gestures each, repeating nine times), each having 16 features linearly interpolated to 80 observations over time.
provides options for both feminine and masculine translations when translating queries that are gender-neutral in the source language. For this work, they have developed a three-step approach, which involved detecting gender- neutral queries, generating gender-specific translations and checking for accuracy.
to the World Bank, “Artificial intelligence could “end famine” by predicting developing crisis before they begin. The World Bank has launched the Famine Action Mechanism (FAM) in collaboration with international organizations such as the Red Cross, Microsoft etc., to use their expertise and services to prevent famines in the future.
is often said that in some countries, their legal system are being utilized by governments and influential parties to oppress the voice of people. Courts are being used to punish citizens for ‘crimes’ such as homosexuality and blasphemy. Courts are also being used as instruments of persecution against those who go against the government or demand their human rights. Video: TrialWatch
3-Factor Iron Triangle A child with a cured cleft lip condition, post operation With AI gaining prominence in many sectors, the health sector is not far behind. AI has been a transformational factor in changing the lives of many people. Using AI-based services has enabled the medical world to reduce costs and improve the outcomes of treatments. https://news.microsoft.com/transform/operation-smile-dignity-children/
of a real dog performing various locomotion skills. Then, we use RL (reinforcement learning) to train a control policy to imitate the dog’s motions. Comparison of policies before and after adaptation on the real robot. Before adaptation, the robot is prone to falling. But after adaptation, the policies are able to more consistently execute the desired skills.
capture clips of a real dog performing various locomotion skills. Then, we use RL (reinforcement learning) to train a control policy to imitate the dog’s motions. A diagram of the workflow of MIT's machine learning programs for vaccine design. The OptiVax algorithm searches for optimal binding pairs of peptides and human cell surface receptor proteins. It is composed of a novel assembly of eleven existing machine learning search programs. Its objective function is the information about optimal population coverage fed to it by the second algorithm, EvalVax, which analyzes frequency of genetic variants across the population. Two versions of each program options in the workflow, a simpler version called Unliked and a more sophisticated version, known as Robust, which tracks not just single variants in human genes but linked sets of variants known as haplotypes. The option to cover haplotypes is an advanced feature that sets the search apart from past efforts. Source
machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks.
streamlined architecture that uses depth-wise separable convolutions to build light weight deep neural networks, mainly focuses on mobile and embedded vision applications. In one word the main focus of the model was to increase the efficiency of the network by decreasing the number of parameters by not compromising on performance. READ MORE - medium.com/datadriveninvestor/review-on- mobilenet-v1-abec7888f438
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