Collaborating Authors

In the battle between AI & Metaverse, CEOs choose AI


According to a new Gartner study, AI is the top priority for business leaders for the third year in a row. The AI market is now on its path to reaching $126 billion by 2025, with no signs of slowing down anytime soon. Hence it's critical for CEOs to grasp the reins and steer their companies into the digital age. Metaverse may be all the rage these days, fuelling popular imagination, taking over movies, games and other pop culture, but when it comes down to the brass tacks, the top bosses at organisations worldwide continue to swear by Artificial Intelligence (AI) to drive global growth. AI has become an inseparable part of an organisation.

Accelerate PyTorch with IPEX and oneDNN using Intel BF16 Technology


Intel and Facebook previously collaborated to enable BF16, a first-class data type in PyTorch. It supports basic math and tensor operations and adds CPU optimization with multi-threading, vectorization, and neural network kernels from oneAPI Deep Neural Network Library (oneDNN, formerly known as MKL-DNN). The related work was published in an earlier blog during the launch of the 3rd Gen Intel Xeon scalable processors (formerly codename Cooper Lake). In that blog, we introduced the HW advancements for native BF16 support in Cooper Lake with BF16- FP32 fused multiply-add (FMA) Intel Advanced Vector Extensions-512 (Intel AVX-512) instructions that bring doubled theoretical compute throughput over FP32 FMA. Based on the HW advancement and SW optimization from Intel and Facebook, we showcased 1.40x-1.64x

New AI Model Translates 200 Languages, Making Technology Accessible to More People


Language is our lifeline to the world. But because high-quality translation tools don't exist for hundreds of languages, billions of people today can't access digital content or participate fully in conversations and communities online in their preferred or native languages. This is particularly an issue for hundreds of millions of people who speak the many languages of Africa and Asia. To help people connect better today and be part of the metaverse of tomorrow, our AI researchers created No Language Left Behind (NLLB), an effort to develop high-quality machine translation capabilities for most of the world's languages. Today, we're announcing an important breakthrough in NLLB: We've built a single AI model called NLLB-200, which translates 200 different languages with results far more accurate than what previous technology could accomplish.

EUMETSAT to explore new artificial intelligence approaches


Determined to remain at the forefront of innovation, EUMETSAT will prioritise using artificial intelligence and machine learning technologies over the next decade in order to best serve its user community. The new strategy, known as the Artificial Intelligence and Machine Learning roadmap, aims to ensure that EUMETSAT uses the most advanced knowledge and technologies in order to optimise its Earth observation satellite programmes, facilitate research and cooperation among its 30 Member States, and strengthen collaboration among partners, international agencies, academia, and businesses. Artificial intelligence is a field in which machines carry out tasks so sophisticated they have typically been thought to require a human brain. These approaches can be used to better integrate different sources of data into decision-making processes as well as to support humans in interpreting Earth observations and issuing life-saving weather warnings.

Microsoft Is Scrapping Some Bad A.I. Facial Recognition Tools


As an outspoken proponent to properly regulate facial recognition technology, MicrosoftMSFT announced it would get rid of its A.I. tools in this space. A.I. is still the most disputed part of technology and is becoming increasingly more commonplace as companies look to incorporate it across their platforms. Now, Microsoft is finally putting an end to its role in the potential for abuse that facial recognition technology has, which could lead to incidents of racial profiling. Following a two year review, and 27-page document, the tech giant wants to have tighter controls of its artificial intelligence products. CultureBanx reported that in the past Microsoft has asked governments around the world to regulate the use of facial recognition technology.

What are the Types of Machine Learning?


Your company's ads target prospective customers, your CRM software delivers insights to sales for funnel optimization, and your chatbots converse with customers--these are all examples of machine learning at work. Machine learning is a type of artificial intelligence that enables computers to imitate human learning processes on their own based on data input. Computers learn from algorithms that programmers develop and the data set that programmers feed into it. In this type of machine learning, a developer feeds the computer a lot of data to train it to connect a particular feature to a target label. A feature could be images or text that the computer matches to an object to identify it.

Break through language barriers with Amazon Transcribe, Amazon Translate, and Amazon Polly


Imagine a surgeon taking video calls with patients across the globe without the need of a human translator. What if a fledgling startup could easily expand their product across borders and into new geographical markets by offering fluid, accurate, multilingual customer support and sales, all without the need of a live human translator? What happens to your business when you're no longer bound by language? It's common today to have virtual meetings with international teams and customers that speak many different languages. Whether they're internal or external meetings, meaning often gets lost in complex discussions and you may encounter language barriers that prevent you from being as effective as you could be.

Meta's massive multilingual translation opus still stumbles on Greek, Armenian, Oromo


"Broadly accessible machine translation systems support around 130 languages; our goal is to bring this number up to 200," the authors write as their mission statement. Meta Properties, owner of Facebook, Instagram and WhatsApp, on Wednesday unveiled its latest effort in machine translation, a 190-page opus describing how it has used deep learning forms of neural nets to double state-of-the-art translation for languages to 202 languages, many of them so-called "low resource" languages such as West Central Oromo, a language of the Oromia state of Ethiopia, Tamasheq, spoken in Algeria and several other parts of Northern Africa, and Waray, the language of the Waray people of the Philippines. The report by a team of researchers at Meta, along with scholars at UC Berkeley and Johns Hopkins, "No Language Left Behind: Scaling Human-Centered Machine Translation," is posted on Facebook's AI research Web site, along with a companion blog post, and both should be required reading for the rich detail on the matter. "Broadly accessible machine translation systems support around 130 languages; our goal is to bring this number up to 200," they write as their mission statement. As Stephanie relates, Meta is open-sourcing its data sets and neural network model code on GitHub, and also offering $200,000 I'm awards to outside uses of the technology.

Director, Data Science


Apex Fintech Solutions (AFS) powers innovation and the future of digital wealth management by processing millions of transactions daily, to simplify, automate, and facilitate access to financial markets for all. Our robust suite of fintech solutions enables us to support clients such as Stash, Betterment, SoFi, and WeBull, and more than 20 million of our clients' customers. Collectively, AFS creates an environment in which companies with the biggest ideas in fintech are empowered to change the world. We are based in Dallas, TX and also have offices in Austin, New York, Chicago, Los Angeles, Portland, and Belfast. If you are seeking a fast-paced and entrepreneurial environment where you'll have the opportunity to make an immediate impact, and you have the guts to change everything, this is the place for you.

Computational Protein Design Scientist


Generate Biomedicines is a new kind of therapeutics company – existing at the intersection of machine learning, biological engineering, and medicine – pioneering Generative Biology to create breakthrough medicines where novel therapeutics are computationally generated, instead of being discovered. Generate has built a machine learning-powered biomedicines platform with the potential to generate new drugs across a wide range of biologic modalities. This platform represents a potentially fundamental shift in what is possible in the field of biotherapeutic development. We pursue this audacious vision because we believe in the unique and revolutionary power of generative biology to radically transform the lives of billions, with an outsized opportunity for patients in need. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!