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1More introduces Omthing range of audio accessories in India

#artificialintelligence

While the name may sound familiar thanks to Carl Pei's new audio brand Nothing that just launched a pair of true wireless earbuds, Omthing is looking to bring affordable luxury audio products to the country. The company is eyeing a 5% share of India's smart wearables market in 3 yrs and is also looking to set up an R&D centre in India. All three products come with a premium design and an IPX4 rating for dust and water resistance. The Omthing AirFree Lace Neckband is available in black colour option and priced at Rs 1,499 is the cheapest of the three. Omthing AirFree TWS earbuds will retail at Rs 2,499 and are also available in black colour only.


Error Detection in Large-Scale Natural Language Understanding Systems Using Transformer Models

arXiv.org Artificial Intelligence

Large-scale conversational assistants like Alexa, Siri, Cortana and Google Assistant process every utterance using multiple models for domain, intent and named entity recognition. Given the decoupled nature of model development and large traffic volumes, it is extremely difficult to identify utterances processed erroneously by such systems. We address this challenge to detect domain classification errors using offline Transformer models. We combine utterance encodings from a RoBERTa model with the Nbest hypothesis produced by the production system. We then fine-tune end-to-end in a multitask setting using a small dataset of humanannotated utterances with domain classification errors. We tested our approach for detecting misclassifications from one domain that accounts for <0.5% of the traffic in a large-scale conversational AI system. Our approach achieves an F1 score of 30% outperforming a bi- LSTM baseline by 16.9% and a standalone RoBERTa model by 4.8%. We improve this further by 2.2% to 32.2% by ensembling multiple models.


Lawsuits say Siri and Google are listening, even when they're not supposed to

Washington Post - Technology News

The judge said that most of the lawsuit could move forward, despite Apple's request to have it thrown out. Judge Jeffrey S. White, of federal district court in Oakland, did dismiss one piece involving users' economic harm. But he ruled that the plaintiffs, who are trying to make the suit a class action case, could continue pursuing claims that Siri turned on unprompted and recorded conversations that it shouldn't have and passed the data along to third parties, therefore violating user privacy.


Futureflix

#artificialintelligence

Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by humans or animals. Leading AI textbooks define the field as the study of "intelligent agents": any system that perceives its environment and takes actions that maximize its chance of achieving its goals. Some popular accounts use the term "artificial intelligence" to describe machines that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving". AI applications include advanced web search engines, recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri or Alexa), self-driving cars (e.g. Tesla), and competing at the highest level in strategic game systems (such as chess and Go), As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect.


Infrastructure Design for Real-time Machine Learning Inference

#artificialintelligence

This is a guest authored post by Yu Chen, Senior Software Engineer, Headspace. Headspace's core products are iOS, Android and web-based apps that focus on improving the health and happiness of its users through mindfulness, meditation, sleep, exercise and focus content. Machine learning (ML) models are core to our user experiences by offering recommendations that engage users with new relevant, personalized content that builds consistent habits in their lifelong journey. Data fed to ML models is often most valuable when it can be immediately leveraged to make decisions in the moment, but, traditionally, consumer data is ingested, transformed, persisted and sits dormant for lengthy periods of time before machine learning and data analytics teams leverage it. Finding a way to leverage user data to generate real-time insights and decisions means that consumer-facing products like the Headspace app can dramatically shorten the end-to-end user feedback loop: actions that users perform just moments prior can be incorporated into the product to generate more relevant, personalized and context-specific content recommendation for the user.


Colby College hires director for artificial intelligence institute

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Colby College has hired a language processing expert to lead its newly formed Davis Institute for Artificial Intelligence. Amanda Stent, considered one of the country's leading authorities on natural language processing โ€“ which gives computers the ability to understand human text and spoken words โ€“ will start in October. Stent most recently served as the natural language processing architect at Bloomberg L.P., where she led the People and Language AI Team. Stent has authored or co-authored more than 100 papers on natural language processing and is a regular speaker on the subject. She was also involved in the CALO (Cognitive Assistant that Learns and Organizes) project that led to a range of AI applications, including the well-known virtual assistant Siri.


Samsung's Premiere 4K projector is $1,000 off right now

Engadget

One of Samsung's latest ultra-short throw projectors has been discounted by $1,000 as part of a larger sale on Amazon. The Premiere Projector with a 4.2.2 channel sound system is down to $5,498 -- yes that's still quite expensive even for a projector, but it's a much better buy now than at it's normal $6,500 price. We've only seen it cheaper in June during Prime Day when it was an additional $300 off. If you feel comfortable sacrificing on sound, the same model with a 2.2 channel system has dropped to $2,998. Samsung's matching both prices, so you could buy direct from the company if you prefer.


The Morning After: Windows 11 will be available (for some) on October 5th

Engadget

Microsoft has announced that Windows 11 will be available on October 5th as a free upgrade for qualifying Windows 10 systems, as well as on new PCs shipping after that date. But it isn't for everyone; a gradual rollout will prioritize newer hardware and use "intelligence models" to determine who gets the upgrade first. Microsoft will apparently factor in reliability and device age. It could be the case that friends and family utterly disinterested in an OS update could be offered it ahead of anyone champing at the bit for the latest edition of Windows. All supporting machines will get the update by mid-2022, if you can think that far ahead.


How Can Artificial Intelligence Benefit Humans

#artificialintelligence

You are in an era where you can see the fast evolution of technology from being reactive to proactive. You are witness to the time when computers are slowly taking up space in every aspect of your life. You will have some form of electronic intelligence around you. Why is the song you hear on your favourite music app driven by algorithms that use artificial intelligence? What is this artificial intelligence, and in what other ways does this technology help?


Multi-Sample based Contrastive Loss for Top-k Recommendation

arXiv.org Artificial Intelligence

The top-k recommendation is a fundamental task in recommendation systems which is generally learned by comparing positive and negative pairs. The Contrastive Loss (CL) is the key in contrastive learning that has received more attention recently and we find it is well suited for top-k recommendations. However, it is a problem that CL treats the importance of the positive and negative samples as the same. On the one hand, CL faces the imbalance problem of one positive sample and many negative samples. On the other hand, positive items are so few in sparser datasets that their importance should be emphasized. Moreover, the other important issue is that the sparse positive items are still not sufficiently utilized in recommendations. So we propose a new data augmentation method by using multiple positive items (or samples) simultaneously with the CL loss function. Therefore, we propose a Multi-Sample based Contrastive Loss (MSCL) function which solves the two problems by balancing the importance of positive and negative samples and data augmentation. And based on the graph convolution network (GCN) method, experimental results demonstrate the state-of-the-art performance of MSCL. The proposed MSCL is simple and can be applied in many methods. We will release our code on GitHub upon the acceptance.