"Q: How worried do you think we humans should be that machines will take our jobs? A: It depends what role machine intelligence will play. Machine intelligence in some cases will be useful for solving problems, such as translation. But in other cases, such as in finance or medicine, it will replace people." This Q&A is taken from Tom Standage's description of how he interviewed AI (language model GPT-2) for The Economist The World in 2020. As readers of this column's annual roundup of AI predictions know, this year's first installment of 120 AI predictions for 2020 featured my interview of Amazon AI in which Alexa performed slightly better than the previous year. For the new list of 99 additional predictions, I repeated Standage's question to Alexa, and got the response "Hmm, I'm not sure." The following AI movers and shakers are a lot more confident in what the near future of machine intelligence will look like, from robotic process automation (RPA) to human intelligence augmentation (HIA) to natural language processing (NLP).

Speechly, a startup out of Helsinki that boasts an experienced team of speech recognition and "natural language understanding" experts, has raised €2 million in seed funding to make it easier for developers to add a voice UI to their products. The round is led by Berlin's Cherry Ventures, with participation from Seedcamp, Quantum Angels, Joyance Partners, Social Starts, Tiny.vc, Juha Paananen (co-founder of Nonstop Games, which exited to King), and Nicolas Dessaigne (founder of Algolia). The funding will be used by Speechly to further develop and open up its API to enable non-experts to create voice-enabled applications. "Voice has shown real promise over the past few years but a real breakthrough beyond setting kitchen timers and playing Spotify is yet to be seen," Speechly co-founder and CEO Otto Söderlund tells TechCrunch. "The current fundamental problem of voice assistant platforms is that they tend to fail with more complex user requests and needs".

The countdown to the biggest tech show on earth is on. Held annually in Las Vegas, the 53rd CES is the place to be if you are interested in next-generation innovations. They say "What happens in Vegas, stays in Vegas"- but not in this case. CES, which stands for the Consumer Electronics Show, first took place in 1967. In the 50 years since, thousands of products have been announced, including many that have transformed the lives of people around the world.

With 51 workshops, 1428 accepted papers, and 13k attendees, saying that NeurIPS is overwhelming is an understatement. I did my best to summarize the key trends I got from the conference. This post is generously edited by the wonderful Andrey Kurenkov. Disclaimer: This post doesn't reflect the view of any of the organizations I'm associated with. NeurIPS is huge with a lot to take in, so I might get something wrong.

WIRE)--Bidgely today introduced the latest version of its UtilityAI Platform for delivering a personalized energy experience to utility customers as well as operational efficiencies for global utilities. As the energy industry's only artificial intelligence (AI) platform for hyper-personalization, Bidgely has developed the world's most accurate and actionable customer energy insights based on actual energy habits that are continuously improved and personalized with each interaction. To highlight the impacts of AI in 2019 and in the years to come, global utilities and energy retailers including NiSource, VSE-RWE, Hydro Ottawa and Origin Energy join Navigant Research and Smart Energy Consumer Collaborative in the video How AI Will Change the Utility Industry. "2019 has been a breakout year for UtilityAI," said Bidgely CEO Abhay Gupta. "Our AI-powered hyper-personalization for utilities is powered by actual insights gained from real world deployments, i.e. 15M homes from 30 utility partners in 15 countries. We continue to expand the Bidgely UtilityAI ecosystem with multiple, global customer engagements in key industry categories. This broadening of our solutions and deepening of each offering is only accelerating as our AI and machine learning algorithms become more powerful and reveal new value to be gained throughout an entire utility's operations."

The artificial intelligence sector sees over 14,000 papers published each year. This field attracts one of the most productive research groups globally. AI conferences like NeurIPS, ICML, ICLR, ACL and MLDS, among others, attract scores of interesting papers every year. The year 2019 saw an increase in the number of submissions. This year also saw noticeable trends like the increased usage of PyTorch as a framework for research increased by 194% among many others.

Hyderabad: As scientific disciplines go, the field of'Deep Learning' is but an infant. However, it will soon have a disruptive effect on the field of drug design, experts say. They were speaking at a panel discussion as part of the ongoing international conference on high performance computing in Hyderabad on Wednesday. Deep learning, a subset of machine learning, functions by imitating the workings of the human brain to process large amounts of data. The artificial neural networks used in these functions have neuron nodes connected together like a web.

In August, Google AI researchers working with the ALS Therapy Development Institute shared details about Project Euphonia, a speech-to-text transcription service for people with speaking impairments. They showed that, using data sets of audio from both native and non-native English speakers with neurodegenerative diseases and techniques from Parrotron, an AI tool for people with impediments, they could drastically improve the quality of speech synthesis and generation. Recently, in something of a case study, Google researchers and a team from Alphabet's DeepMind employed Euphonia in an effort to recreate the original voice of Tim Shaw, a former NFL football linebacker who played for the Carolina Panthers, Jacksonville Jaguars, Chicago Bears, and Tennessee Titans before retiring in 2013. Roughly six years ago, Shaw was diagnosed with ALS, which requires him to use a wheelchair and left him unable to speak, swallow, or breathe without assistance. Over the course of six months, the joint research team adapted a generative AI model -- WaveNet -- to the task of synthesizing speech from samples of Shaw's voice prior to his ALS diagnoses.

It has been quite a year for legal tech startup Evisort. Twelve months ago this week, the company introduced its flagship product, Document Analyzer, a cloud-based AI and text-mining application that helps enterprises analyze and manage their contracts. At the time, I wrote that it "might just be the hottest legal tech and AI company you've never heard of." After launching with angel funding from Amity Ventures, an early-stage venture capital firm, and Village Global, a VC firm whose backers include Bill Gates, Mark Zuckerberg, Jeff Bezos and Reid Hoffman, the company earlier this year raised another $4.5 million in seed funding. Now today it is announcing that it has closed a Series A funding round of $15 million.

Severe weather is impacting agriculture across the globe. The Midwestern United States has been continually flooding since March, inflicting $2.9 billion in property damage and threatening the livelihoods of farmers throughout the region. Internationally, food security is under threat from an onslaught of drought, while agriculture is already subject to the challenges of thin margins and complex global trade. Meanwhile, there is increasing pressure to do more with less to ensure food security for the growing global population. To meet these pressures, farmers are driven to get the most out of every harvest, even if that short-term focus may have long-term ill effects on the soil and ultimately their yield.