Sequence-to-sequence(seq2seq)[1] is a versatile structure and capable of many things (language translation, text summarization[2], video captioning[3], etc.). For a short introduction to seq2seq, here are some good posts: [4][5]. Sean Robertson's tutorial notebook[6] and Jeremy Howard's lectures [6][7] are great starting points to get a firm grasp on the technical details of seq2seq. However, I'd try to avoid implementing all these details myself when dealing with real-world problems. It's usually not a good idea to reinvent the wheel, especially when you're very new to this field.

Chinese messaging app WeChat has reportedly apologised after an AI error resulted in it translating a neutral Chinese phrase into the n-word. The WeChat error was reported by Shanghai-based theatre producer and actor Ann James, a black American. In a post on the service's Twitter-like Moments feature, she wrote that it had translated hei laowai – a neutral phrase which literally means "black foreigner" – as the n-word. "We're very sorry for the inappropriate translation," a WeChat spokesperson told Chinese news site Sixth Tone. "After receiving users' feedback, we immediately fixed the problem."

Very often it is only a matter of time before something in science-fiction becomes science-fact. This past week tech giant Google held an event in San Francisco where it unveiled products like the Google Home Mini, a new Chromebook, and its new version of the Google Pixel phone. One of the most intriguing announcements at the event was Google's new Pixel Buds which are reportedly capable of translating up to 40 different languages by using the Google Translate technology. Regarding the Pixel Buds, media sources have made a number of allusions to Douglas Adam's Hitchhiker's Guide to the Galaxy and its Babelfish that allowed anyone to understand any language simply by putting a fish into their ear. Artificial intelligence has enabled this concept to come out of the realm of fiction and into reality.

IF YOU have a Google Pixel phone, you will soon be able to speak 40 languages. All you need is a pair of the earbuds Google announced last week in San Francisco. These can be used to make phone calls and listen to music – but they also provide on-demand two-way translation. To talk in one of the supported languages, you use the earbuds to access Google Assistant and the Google Translate app. Pressing on the earbud and saying "let me speak German", for example, initiates translation of your speech into German, playing the results on the phone's speakers.

Deepgram, a startup applying machine learning to audio data, is releasing its machine transcription platform this morning for free. No more will you have to pay for other services like Trint to get the dirty work of automated transcription done. Hint: it has something to do with data. In fact, machine anything isn't solved. And it seems like everyone these days is making haste to build their own Fort Knox of data to solve machine everything.

Deepgram, a startup applying machine learning to audio data, is releasing its machine transcription platform this morning for free. No more will you have to pay for other services like Trint to get the dirty work of automated transcription done. Hint: it has something to do with data. In fact, machine anything isn't solved. And it seems like everyone these days is making haste to build their own Fort Knox of data to solve machine everything.

Google has built a pair of headphones that can translate foreign languages in real time. The Pixel Buds are like a real-world equivalent of the Babel fish, the famous fictional creature from The Hitchhiker's Guide to the Galaxy. They both translate and enable you to speak in foreign languages, and worked incredibly impressively in a demo at Google's launch event this week, enabling an English speaker to hold a smooth conversation with a Swedish speaker. "It's like you've got your own personal translator with you everywhere you go," says Google. "Say you're in Little Italy, and you want to order your pasta like a pro. All you have to do is hold down on the right earbud and say, 'Help me speak Italian'. As you talk, your Pixel phone's speaker will play the translation in Italian out loud. When the waiter responds in Italian, you'll hear the translation through your Pixel Buds."

Since its latest edition, the Google Translate application now supports over 100 languages and serves a worldwide community of over 500 million users virtually. But over 6,000 languages are actually spoken, with around 360 languages spoken by a million people or more. To combat this disparity in translation technology, the USC Information Sciences Institute is working on a universal language translation system. Supported by the Defense Advanced Research Projects Agency, the program involves ISI Director of Natural Language Technologies Kevin Knight and a small team of full-time researchers and doctoral students. Knight has worked with ISI in natural language processing for 25 years, and the system is one of many projects he's working on in the field.

We are in a great time with regards to AI and Machine Learning, due to immense interest and the pace of technological advances. Recent papers show that gradient descent will asymptotically avoid saddle points and it can take exponential time to escape saddle points. Jia Li, Head of R&D, Cloud AI and Machine Learning, Google gave an inspirational keynote on "Why democratizing AI matters: Computing, data, algorithms, and talent". Talking about algorithms, she mentioned that her team switched from phrase-based machine translation to Neural Machine Translation (NMT), and this has led to many improvements.

Last week, experts from the AI world came together for the Artificial Intelligence Conference at San Francisco to discuss insights, opportunities, challenges and trends related to the rapidly expanding field of AI. The conference included hands-on trainings, tutorials, startup showcase (which was won by PipelineAI), keynotes, sessions, expo, and social events. Here is my report on Key Takeaways from AI Conference in San Francisco 2017 – Day 1. Michael Jordan, Distinguished Professor, UC Berkeley gave his keynote on "How to escape saddle points efficiently". We are in a great time with regards to AI and Machine Learning, due to immense interest and the pace of technological advances. However, the theories and our understanding is lagging to keep up with the challenges.