Hanson: OK Geoff, thanks for joining me in this chat. This is for AIhub, and I've recorded three or four different conversations and it sort of started out thinking about– what is AI, but it really started out with an old friend of mine (we overlapped in Graduate School), Michael Jordan, who had written several articles (one in Medium) and I wrote a reply, which got some attention, mainly from Mike. He and I had this discussion and I disagreed so much with him I wanted to just see what was going on. Even if you haven't been paying attention you'll notice that something is happening. He was basically saying that the deep-learning phenomenon that's happening right now is – I almost think of it as like The Beatles, when Beatlemania started, we're in deep-learning mania. But, there's a lot of good things happening too, and as I pointed out to him, protein folding.. He said "I agree, but of course, they didn't solve the problem!". I said "you're creating these diminishing comments to create an atmosphere of'this is going to fail, the AI winter is going to come'. Why are you doing this? Don't you realize you're like the only person who doesn't get this". Hanson: Now I know that because I've debated him back in the 80s!, I will warn you this is a Gary Marcus free zone and I'm not going to talk about him. Hinton: In 2015 he made a prediction that computers wouldn't be able to do machine translation. Hanson: Yes, I know, but Gary is the most inconsistent… consistently inconsistent person I know. I wish people would stop taking him so seriously. Anyway, I knew Michael back in grad school and at that point he was always focused on the margins of things – I mean, important things. There's a sense in which he really is rejecting the whole DL thing strongly, and he's an interesting character in this. Now, you on the other hand have had, at least what I've heard you say in other contexts, that deep learning concerns you. I think that Yoshua Bengio has had a lot of concerns as well about DL. So we're doing classification and it works well, but how does it compare to human thought and reasoning, and all the wonderful things humans do?

Welcome to our first monthly digest of 2022! This is the place where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we cover our new series New voices in AI, hear from an ACML award winner, and celebrate an arXiv milestone. We're excited to announce the launch of a new series for AIhub: New voices in AI. Hosted by Joe Daly, this series will highlight the work of PhD students, early career researchers, and those in the field of AI with a fresh perspective.

The DONUts platform may look like a collection of bronze-colored, futuristic coffee cups, but everything becomes clearer as they begin to move. The group of modular robots dance in a well-choreographed symphony as magnets turn on and off allowing the modules to pull or push their neighbors. Using these simple interactions, the modular robots can achieve complex tasks such as energy harvesting [1]. Nialah Wilson is one of the key roboticists who helped bring these modular robots to life. Taking advantage of the right message, passed at the right time, is also one of the things that led to Nialah's career in robotics.

Frost & Sullivan, a leading management consultancy supporting clients on their journey to visionary innovation and transformational growth, announced that it has honored Startek a global provider of customer experience (CX) management solutions, with the 2021 Americas New Product Innovation Award for customer experience outsourcing services. "Companies must move forward with centralized data and automated tasks and interactions through self-service tools," said Sebastian Menutti, industry principal, Frost & Sullivan. "But, human agents must still be available when intuition, emotional intelligence, and empathy are required to deliver positive customer outcomes. This award recognizes the Startek approach that seamlessly combines live agent interactions with digital solutions to deliver added benefit for their customers." Startek enables its partners to integrate digital technologies and live interactions to deliver best-in-class CX.

My wife, who rounds in the hospital and teaches, often tells me that if more people really understood what the medical professionals see and what they must do, this just might alter their perspective on how they lead their lives. With real experience often comes better understanding. And yet, when you can't fully experience something, perhaps the best alternative is to learn from someone who is able to clearly and compellingly teach. Arriving Today, by distinguished science writer and Wall Street Journal technology columnist Christopher Mims, is one of those books that is able to tell the incredible story of what happens when you order a new USB charger, from the point of origin to the point of delivery, on that UPS truck. Imagine watching a movie where you follow this USB, and as you journey to each new location Christopher teaches you chapter by chapter about the history of technology, the origins of the ideas behind what he sees, the numbers that back them all up, and the stories of the people who are impacted greatly by all of this.

Welcome to the first episode of New voices in AI! You can find David on Twitter @davlanade and find out more about Masakhane here. The music used is'Wholesome' by Kevin MacLeod, Licensed under Creative Commons Daly: Hello and welcome to new voices in AI, this a new series from AIhub where we celebrate the voices PhD students, early career researchers, and those with a new perspective on AI. And without further ado, let's begin. First up, a big welcome to our very first guest on "New voices in AI" and if you could introduce yourself, who are you? Adelani: Thank you very much for having me. So, Masakhane is this grassroots organization, whose mission is to strengthen and spur NLP research in African languages, by Africans for Africans, so, and currently the organization we are majorly operating on Slack we already have over 1000 Members. Of course, not everyone is active but we have more than 100 or close to 100 active members as well, yeah. So how did, how did you get into AI?

Jasper Health is a fast-paced company with a noble mission to provide a digital experience to improve the lives of cancer patients and their caregivers throughout their treatment and remission journeys. The company announced its official launch and was covered by high impact media outlets including USA Today, and HIT Consultant. A few months later, Jasper announced its first large-scale client with Employer Direct Healthcare which covers over 2MM lives across hundreds of employers. Jasper Health is funded and supported by Redesign Health, with a recent round of funding led by 7wire Ventures, known for such digital health stand outs as Livongo, which merged in an $18.5 billion transaction with Teladoc late last year. We are currently focused on the 100M patients living with cancer, as well as their loved ones who provide care and support throughout treatment and recovery.

Language models increasingly rely on massive web dumps for diverse text data. However, these sources are rife with undesirable content. As such, resources like Wikipedia, books, and newswire often serve as anchors for automatically selecting web text most suitable for language modeling, a process typically referred to as quality filtering. Using a new dataset of U.S. high school newspaper articles -- written by students from across the country -- we investigate whose language is preferred by the quality filter used for GPT-3. We find that newspapers from larger schools, located in wealthier, educated, and urban ZIP codes are more likely to be classified as high quality. We then demonstrate that the filter's measurement of quality is unaligned with other sensible metrics, such as factuality or literary acclaim. We argue that privileging any corpus as high quality entails a language ideology, and more care is needed to construct training corpora for language models, with better transparency and justification for the inclusion or exclusion of various texts.

Recommender systems are among the most pervasive machine learning applications on the Internet. Social media, audio and video streaming, news, and e-commerce are all heavily driven by the data-intensive personalization they enable, leveraging information drawn from the behavior of large user bases to offer a myriad of recommendation services. Point of Interest (PoI) recommendation is the task of recommending locations (business, cultural sites, natural areas) for a user to visit. This is a well-established sub-field within recommender systems, and as a domain of application, it provides a good introduction to the challenges of applying personalized recommendation in practical contexts. An effective PoI recommender must consider a user's interests and preferences, as in any personalized system, but also practical aspects of travel: weather, congestion, hours of operation, seasonality, to name a few.

Digital banking continues to grow in momentum and importance. Jacquie Hersch, head of industry marketing for financial services at ServiceNow, joins us to discuss digital transformation and how banks can offer even more effective digital products and services. Below is a full transcript of my interview with Jacquie Hersch. Welcome to the BAI Banking Strategies podcast. I've been looking forward to it. Jacquie, ServiceNow recently collaborated Aite-Novarica on a white paper titled "Transforming the Banking Experience Through Digital Growth."