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Last year, we identified blockchain, cloud, open-source, artificial intelligence, and knowledge graphs as the five key technological drivers for the 2020s. Although we did not anticipate the kind of year that 2020 would turn out to be, it looks like our predictions may not have been entirely off track.

Also: 2021 technology trend review, part one: Blockchain, cloud, open source

Let's pick up from where we left off, retracing developments in key technologies for the 2020s: Artificial intelligence and knowledge graphs, plus an honorable mention to COVID-19-related technological developments.

In our opener for the 2020s, we laid the groundwork to evaluate the array of technologies under the umbrella term "artificial intelligence." Now we'll use it to refer to some key developments in this area, starting with hardware.

The key thing to keep in mind here is that the proliferation of machine learning workloads has boosted the use of GPUs, previously used mostly for gaming, while also giving birth to a whole new range of manufacturers. Nvidia, which has come to dominate the AI chip market, had a very productive year.

First, by unveiling its new Ampere architecture in May, Nvidia claims this brought an improvement of about 20 times compared to Volt, its previous architecture. Then, in September, Nvidia announced the acquisition of Arm, another chip manufacturer. As we noted then, Nvidia's acquisition of Arm strengthens its ecosystem and brings economies of scale to the cloud and expansion to the edge.

As others noted, however, the acquisition may face regulatory scrutiny. The AI chip area deserves more analysis, on which we'll embark soon. However, some honorable mentions are due: To Graphcore, for having raised more capitaland seen chips deployed in the cloud and on-premise; Cerebras, for having unveiled its second-generation wafer-scale AI chip; and Blaize, for having released new hardware and software products.

The software side of things was equally eventful, if not more. As noted in the State of AI report for 2020, MLops was a major theme. MLOps, short for machine learning operations, is the equivalent of DevOps for ML models: Taking them from development to production, and managing their lifecycle in terms of improvements, fixes, redeployments, and so on.

AI has made progress in 2020, by means of opening up to a more well-rounded approach. But it has also seen setbacks.

Some of the more popular and fastest-growing Github projects in 2020 are related to MLOps. Streamlit, helping deploying applications based on machine learning models, and Dask, boosting Python's performance and operationalized by Saturn Cloud, are just two of many examples. Explainable AI, the ability to shed light on decisions made by ML models, may not be equally operationalized but is also gaining traction.

Another key theme was the use of machine learning in biology and healthcare. AlphaFold, DeepMind's system that succeeded in solving one of the most difficult computing challenges in the world, predicting how protein molecules will fold, is a prime example. More examples of AI having an impact in biology and healthcare are either here already or on the way.

But what we think should top the list is not a technical achievement. It is what's come to be known as AI ethics, i.e. the side-effects of using AI. In a highly debated development, Google recently "resignated" Timnit Gebru, a widely respected leader in AI ethics research and former co-lead of Google's ethical AI team.

Gebru was essentially "resignated" for uncovering uncomfortable truths. In addition to bias and discrimination, which Gebru posits is not just a side-effect of datasets mirroring bias in the real world, there is another aspect of what her work shows that deserves highlighting. The dire environmental consequences that the focus on ever bigger and more resource-hungry AI models has. DeepMind's dismissal of the issue in favor of AGI speaks volumes on the industry's priorities.

We did say "bigger and more resource-hungry AI models," and this bill fits perfectly another one of 2020's defining moments for AI: Language models. Besides costing millions to train, these models also have another issue: They don't know what they are talking about, which becomes clear if scrutinized. But if this is the state of the art in AI, is there a way to improve upon it? Opinions vary.

Yoshua Bengio, Yann LeCunn, and Geoffrey Hinton are considered the forefathers of deep learning. Some people subscribe to Hinton's view, that eventually all issues will be solved, and deep learning will be able to do everything. Others, like Gary Marcus, believe that AI, in the way it is currently conflated with deep learning, will never amount to much more than sophisticated pattern recognition.

Marcus, who has been consistent in his critique of deep learning, and language models based on it, is perhaps the most prominent among the ranks of scientists and practitioners who challenge today's conventional wisdom on AI. In a high profile encounter in December 2019, Marcus and Bengio debated the merits and shortcomings of deep learning and symbolic AI.

This may well have served as a watershed moment since a number of developments have elapsed since that seem to point to cross-pollination between the data-driven world of deep learning and the knowledge-driven world of symbolic AI. Marcus published a roadmap toward a merger of the two worlds, what he calls robust AI, in early 2020.

With 2020 having been what it was, this work may not have gotten the acclaim it would normally have, but it was not a shot in the dark either. Marcus elaborated on this work, as well as background and implications, in an in-depth conversation we hosted here on ZDNet. Marcus' line of thought is not singular either -- similar ideas also go by the name of Neurosymbolic AI.

A hybrid model for AI, combining machine learning and a knowledge-based approach, is gaining traction. Image: A. Ananthaswamy / Knowable Magazine

Bengio on his part published work on topics such as exploiting syntactic structure for better language modeling, factorizing declarative and procedural knowledge in dynamical systems, or even learning logic rules for reasoning on knowledge graphs in 2020. This seems like a tangible recognition of a shift toward embedding knowledge and reasoning in deep learning.

Marcus himself identified the important role knowledge graphs can play in bridging the two worlds. Knowledge graphs are arguably the best widely available and understood technology we have today for knowledge representation and reasoning, except language. Besides reaching peak hype in Gartner's hype cycle for AI in 2020, knowledge graphs are increasingly being adopted in real-world applications from industry leaders to mid-market companies.

But there is another use of graphs that has blossomed in 2020: Graph machine learning. Graph neural networks operate on the graph structures, as opposed to other types of neural networks that operate on vectors. What this means in practice is that they can leverage additional information.

Graph machine learning also goes by the name of geometrical machine learning, because of its ability to learn from complex data like graphs and multi-dimensional points. Its applications in 2020 have been pertinent in biochemistry, drug design, and structural biology. Knowledge graphs and graph machine learning can work in tandem, too.

Last year was undoubtedly characterized by the advent of COVID-19. While COVID-19 may have catalyzed digital transformation, remote work, applications in biology, healthcare, artificial intelligence, and research, not all of its side-effects were positive.

COVID-19 has also catalyzed technological applications such as thermal scanners, face recognition, immunity passports, and contact tracing, the use of which often comes with strings attached. While this is not unlike other technologies, what makes COVID-19-related technological applications stand out is their pervasiveness and the speed at which they have been deployed.

Like all other technological drivers, COVID-19 has been a mixed bag for technological progress and adoption. The speed of adoption of related technologies, however, means that society at large is lagging in terms of an informed debate and full comprehension of the implications. Let's hope that 2021 can bring more inclusion and transparency to the table.

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2021 technology trend review, part two: AI, knowledge graphs, and the COVID-19 effect - ZDNet

Aarik Danielsen|Columbia Daily Tribune

Very little escapes Claire Wahmanholm's attention at least as we encounter her on the page.

The Twin Cities-based poet, whose books include 2018's "Wilder" and 2019's "Redmouth," sees nature's seams, its abundance and scarcity, its combustion points and then writes them into the permanent record in devastatingly beautiful dispatches.

Turning her phrases to gazeat creatures who look and act like her, Wahmanholm avoids elevating humans above the rest of the natural order; rather, she places us in context, mercifully granting a greater understanding ofour place within the wilder world. And, in acts of confession, she identifieswhere we've abdicated our end of the bargain that creates harmony.

Thursday, Wahmanholm will participate in a virtual reading as part of the Unbound Book Festival, which has moved from one in-person weekend to four months of online events in response to the COVID-19 pandemic. Ahead of the reading, she traded emails with the Tribune to discuss how a heightened sense ofmortality impacts her work, parenthood as an act of attention and poetry and much more.

Tribune: Youll be participating in this reading with peer poets Jenny Xie and Jay Deshpande. How do events like these tend to nourish your own creativityperhaps especially at a time of relative isolation?

Wahmanholm: This event is coming at a really welcome time for me: this past fall was such a rough one. It ended up being the most inhumane semester of my teaching career (I dont think this is an uncommon feeling among educators). No one, teacher or student, was doing their best work, and morale was very low across the board. Preparing for and getting through each individual day became my only focus I could barely look ahead to the end of a week.

Needless to say, I wasnt connecting with my own poetry or anyone elses. Im really grateful to be returned to poetry in this way. And group readings are always so much more fun than solo ones I love hearing how themes or images or even sounds carry and warp from one poet to the next. I love the polyphony.

Tribune: Something that strikes me in your work is the way you unite yourself (or humanity, more generally) to nature. Were used to poets personifying nature; you almost do this in reverse writing of us in elemental, wild terms. What are the particular challenges and joys of recognizing your own smallness (and oneness), then putting that on the page?

Wahmanholm: Personification is sometimes spoken about as an elevating practice that it elevates nature to the level of humanity. Which is a horrible and backwards way to think about it, of course. Acting like were big and special has had devastating consequences, so I see the insistence on our smallness as an ethical orientation.

During my exam year at my Ph.D program, I remember talking to one of my committee members (the ecologist Nalini Nadkarni) about how being human is so deeply painful because we are uniquely cursed with consciousness (or something), and she was like, Oh I would never say that consciousness is unique to humans how could you even claim that?

And I was like … OH. And felt like an idiot, of course, but in a good way. And that idea has since never been far from me.

I have a pretty gripping fear of death, and I spend a lot of time grieving over the fact that Ill be dead someday, which Im perfectly aware is a waste of energy, but which I also cant help. Being dead is a state that is fundamentally incompatible with human experience/perception/schemas, and in that way, maybe shares something with the consciousnesses of the non-human world. So becoming more elemental, as you say, is as close as I can come to imagining death. Its a way of softening it for myself, maybe. Its a kind of exposure therapy. Writing through it and then seeing it reflected back at me fills me with vertigo and dread, but the more I do it the more at peace I hope to be (it hasnt worked yet, but no harm trying!).

Tribune:Its surprisingly easy for us to forget the Earth especially at moments like this, where it feels like were all just trying to get by. How might poems especially yours be uniquely capable of reminding us that our flourishing and natures flourishing are one and the same?

Wahmanholm:Its funny as a parent of two young children, I find it really hard to forget the Earth. Parenthood returned my eye to what we might think of as the more mundane aspects of nature.

When I was out on walks with my children and trying to introduce them to the world, I found myself being like LOOK AT THIS NEAT PIECE OF BARK, KIDS or ISNT THAT A BEAUTIFUL ANT? And then Id be like, huh, that bark is actually pretty neat. Like how they say teaching something is the best way to learn it.

But parenthood also brought the future into very sharp relief. So much of childrens books are about the natural world, introducing children to the dramatis personae of the animal kingdom, etc. Im reading through all these alphabet books, and Im like, are rhinoceros even going to be around when my children grow up? So the Earth has played a central part of my consciousness over the last four years or so.

But the pandemic has elevated it, too. Weve been newly grateful for the parks and outdoors spaces we have near us, urban though they are. Especially since, on balance, its safer to be outside, those spaces have been serious refuges. When we cant get out, weve been doing a lot of nature shows; last year we watched the "Our Planet" series, which, I discovered, is far more pointed in its ethical orientation than your standard BBC nature documentary.

Like, just as you think youre going to have fun watching the animals just vibing in their element, David Attenborough comes on and is like BECAUSE OF HUMAN ACTIVITY, THESE ADORABLE MARMOSETS WILL ALL BE DEAD NEXT WEEK. And I mean, hes not wrong just because something is grim doesnt make it untrue. And I dont necessarily want to shield my children from that information. But its also a lot. So oof, the Earth is always on my mind. I do think that poems are especially well-suited for reminding us of our inextricability from the rest of the natural world, and I guess I see parenthood as one long, wounding, beautiful poem in that way.

Tribune: Apoem likePreservecoaxes beautiful passages of music and silence from a forest. Im curious about the role of attention in a poem like this. Do you feel immediately attuned to these qualities while present in nature, or do they reveal themselves upon further reflection?

Wahmanholm:I'm interested in the directionality there; I actually see it in reverse that the forest is coaxing those things out of me.

And I love the word attune here to bring into right pitch, right relation; but it comes from atone which in turn comes from the phrase at one. My fear of death is really a fear of becoming unattached from the world, and so Im always finding ways to re-anchor myself to it (even while knowing that death is probably as close to at-onement with nature as were likely to have). Anyway I try to be as deeply attuned as I can at all times. Its probably an impossible but hopefully not an unworthy aim.

But in terms of process, I dont usually write while in the middle of experience most of my place-centric poems are constructed from memory. Sometimes I remember things clearly, and sometimes I rely on guesswork. Ill try out various phrases/images/combinations of words to see if they feel authentic to the memory.

Does songbird bindle match? Does a tingling like my lungs are falling asleep return me to the feeling of that particular place? If no, I try out different combinations until one feels familiar.

Tribune:Whether its in your alliterated poems, more formally inventive pieces or even the use of words like re-spool, theres often a playfulness to your use of language. What balance have you negotiated, or are you negotiating, between substance and style in your work? Between keeping language alive and capturing the readers emotions?

Wahmanholm:I find that keeping language alive and capturing the readers emotions actually reinforce/elevate each other, rather than being in tension with each other. For me, the music of a poem functions as a sort of subconscious, a sort of weather. Weather isnt really content, but it affects a moment nevertheless.

The way I think about it, one thing a poems music can do is carry you over a rift in your understanding. Hopkins is one of my all-time favorite poets for just this reason. Like, do I understand 100% of what Hopkins is about? Nope! But his music, his density, his weirdness, supplies enough of the atmosphere or tone that Im still able to be emotionally devastated by his work. The music is the gesture that says "follow me." It is a generosity.

A poem cannot (should not?) promise to be comprehensible to all readers at all times, but the music of a poem helps you inhabit the poem even without complete comprehension, which is a gift.

If I can return to the idea of attunement: using surprising or playful language is a way for me to be more attuned to the world. I am endlessly astonished by my existence, so I try as hard as I can to capture that astonishment and surreality in my language.

Tribune:Whats one line of poetry that youre really captivated by or proud of at the moment?

Wahmanholm:I've been catching up on a lot of books I acquired last fall but wasnt able to dig into until this month. One of these is S. Brook Corfmans "My Daily Actions, or The Meteorites." The penultimate poem in the book ends When I opened the door, I had my phone to my ear, still locked, to show whatever was coming from the other side that I was not alone, which just totally knocked me over, and which Im still haunted by.

Find out more about Thursday's panel at unboundbookfestival.com.

adanielsen@columbiatribune.com

573-815-1731

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Poet brings deep sense of connection to virtual Unbound date - Columbia Daily Tribune

The Big Bang Theory may be about "nerds" and their dating woes, but the sitcom has covered serious subject matter, from bullying to intimacy issues.

CBS'The Big Bang Theory was much more than a show about "that really smart guy" and his friends. Sheldon and co. took viewers on a ride through relationship mishaps, work adventures, and personal achievements for 12 seasons. While science was always on the minds of Sheldon, Leonard, Raj, and Howard, friendship was at the heart of the show.

RELATED:The Big Bang Theory: Worst Thing About Each Main Character

The sitcom covered far more than just scientific findings and relationship goals; deep issues were tackled in various episodes. Every character had their own strengths and weakness that were highlighted as time went on, and they all learned from each other. Likewise, viewers related to these deep issues and commended the show for its authenticity.

Leonard, Howard, Raj, and Sheldon are all incredibly smart men who have dedicated their lives to science. Their adult lives are full of positivity and friendship but it hasn't always been that way. Everyone (except for Penny) was bullied in their youth. And sadly, the bullying continued.

Penny's ex-boyfriend bullied Sheldon and Leonard on two occasions: when they tried getting her TV back from him and when Leonard tried getting him topay Pennythe money he borrowed from her. In "The Speckerman Recurrence," Leonard also confronted his bully from high school.

The closer Sheldon and Amy became, the more Sheldon opened up to her and showed her the inner workings of his world. He claimed to be a man of the mind, someone who lived minimally and focused on science, but that turned out to be a facade.

RELATED:The Big Bang Theory: Sheldon's 5 Best Pieces Of Advice (& His 5 Worst)

While Sheldon truly diddevote his life to science, he also had a problem with hoarding. He told Amy that the thought of getting rid of his belongings gave him anxiety. He had trouble parting with everything he owned. Luckily for him, Amy let him know there was nothing to be ashamed of and that they could work on his attachment issues slowly.

Everyone isn't as free and open in relationships as Penny and Howard were. Others were a little more reserved and felt vulnerable about getting intimate. Amy was ready for the next step in her relationship with Sheldon but he wasn't ready until they were dating for over five years. Sheldon and Amy proved that every relationship goes at their own speed and that there shouldn't be pressure on a person if they're simply not ready.

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The Big Bang Theory: 10 Times The Show Tackled Deep Issues - Screen Rant

In 2020, the Covid-19 pandemic and the protests that followed the senseless death of George Floyd in Minneapolis made millions reflect on their own role in perpetuating social inequity and systemic racism. In 2021, we will act on that newly understood responsibility. We will work across sectors, disciplines and industries to deepen our understanding of systemic problems and collaborate to find meaningful solutions.

This will lead to real change in science and technology. In 2019, Black people made up only three per cent of the UK tech workforce and only 2.6 per cent of UK technology company board members are from ethnic-minority backgrounds. Attempts to address this critical lack of representation have often been siloed and seen as only a nice to have. In 2021 they will be a key focus of companies strategies.

Throughout the sector, organisations will move from commitments and aspirations to outlining actionable strategies for increasing internal representation. There will be a stronger emphasis on stripping the bias out of candidate sourcing, hiring, promotions and performance reviews. In particular, companies will be more proactive about reaching outside of their traditional networks to identify outstanding talent from less traditional backgrounds.

In academia and other fields that require postgraduate-level qualifications, such as AI, concrete steps will be taken to increase the numbers of Black people choosing, and given the opportunity, to study science and technology.

This is crucial, because disparities set in long before someone submits a job application or even enters the classroom. In the UK, only 2.2 per cent of school teachers, 0.65 per cent of university professors, and 15 of the 445 people who graduated with postgraduate research degrees in computer science in 2018/19 are Black. This challenge is compounded by narrow curriculums, insufficient role models in leadership positions, a lack of options for promising students and minimal funding for postgraduate study and network-based PhD admissions processes.

There will be a focus on supporting Black students attainment in maths and science at GCSE and A Level, and admissions processes at universities will be made fairer. In universities, there will be more support for Black students to progress from Bachelors to Masters to PhD, work-experience schemes supporting Black graduates will be expanded and support for early-career Black researchers will increase.

Many organisations are doing great work: OpenAI offers scholarships to people from under-represented groups who want to study deep learning, and DeepMind, which I work for, has collaborated with more than 20 universities around the world to expand its own scholarship programme which is focused on increasing representation at the postgraduate level through mentorship and financial support.

Beyond education, charities and other organisations working to address racial injustice in the sector and create opportunities for Black scholars such as Data Science Africa, Black in AI and Colour in Tech will see increasing support and engagement.

In 2021, the science and technology sectors will stop looking for quick fixes to address under-representation. Organisations will collaborate across sectors to proactively remove barriers to access and articulate a vision of life for Black people in science and technology at every level. In 2021, we will start to see meaningful change.

Obum Ekeke is global lead, university relations & education partnerships at DeepMind

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Tackling tech's big diversity problem starts with education - Wired.co.uk