academics-from-the-united-kingdom

"Tolkien has become a monster, devoured by his own popularity and absorbed into the absurdity of our time. The chasm between the beauty and seriousness of the work, and what it has become, has overwhelmed me. The commercialization has reduced the aesthetic and philosophical impact of the creation to nothing. There is only one solution for me: to turn my head away."

"The Truth-Seeking Vision insists that the university’s overriding aim should be the preservation, pursuit, and promotion of truth.The Truth-Seekers further believe that the importance of that aim justifies the frictions and rivalries that inevitably arise, especially in demanding intellectual environments populated by brilliant but eccentric individuals more prone than most to idiosyncratic behaviour.By contrast, the Coddling Vision insists that although truth-seeking is a laudable and important aim, it should never supersede the greater goal of pursuing equality, diversity, and inclusion, or of maximising the psychological wellbeing of its members.As it happens, the Truth-Seeking Vision and the Coddling Vision do not come into open conflict quite as often as breathless press reports might lead one to imagine, though that is because tensions are almost always quietly resolved in favour of the Coddlers. Towards the end of last year, however, something unexpected happened: a few dozen of the Truth-Seekers, led by the indefatigable analytic philosopher Arif Ahmed, forced a series of votes challenging a brazen attempt by the University’s senior leadership to wire the Coddling Vision into the ancient fabric of Cambridge."

"I think it’s a great idea to develop AI talent outside of traditional hubs like the Bay Area. Personally, I’m from Nigeria, so I see the value in growing research and innovation in regions that might not be the typical focus."

"Or huge vision models that we call true resolution that allow you to do medical images without reducing the resolution to make the image more blurry, so that you can fit it into the memory requirements of conventional systems."

"And again, you want to be able to handle those large embedding tables because the larger the embedding table, the more accurate the model, the better recommendation you’re able to give."

"For instance, huge natural language processing models for the financial sector or for developing chatbots and customer services, voice-based commerce. Also, natural language processing, finds use in cancer research also."

"What SambaNova brings to the table is the ability one or two or a quarter rack of capability to be able to provide terabytes of memory. And so that allows you to build huge models that can serve any of the particular industrial verticals or commercial verticals that are of interest."

"The whole goal is, of course, to provide the capabilities to be able to train very, very large, accurate models. If you look at the current landscape of computing capabilities, mostly dominated by GPUs, what you need is many, many GPUs because of the limited amount of memory that each of the GPUs can have."

"So think of SambaNova systems as this capability of doing training and inference very efficiently. And then the real full circle: Once you can do training and inference on the same platform, you can dynamically switch between them."

"I am a self-made entrepreneur. I started off as a small-time writer, now I own publishing and IT companies. I do what the hell I want to do."

"The idea of AI replacing politicians is far-fetched, but AI can certainly influence how politics work."

"And so what you want is the capability to both do large batch training very efficiently, but also to single-batch inference very efficiently. And so we can do that with the SambaNova systems."

"I’m deeply concerned about the political response to climate change. The failure to address it is one of the most pressing issues facing humanity today. Politicians often avoid making difficult decisions, choosing short-term gains over long-term solutions. I think we need leaders who will make the tough choices, like former President Obama tried to do, but unfortunately, this is a challenge that’s far from being solved."

"AI’s potential to replace jobs is one of the biggest societal challenges. Just like how the industrial revolution reduced the need for physical labor in factories, AI and automation are making certain jobs obsolete. This raises crucial questions about the future of work and how society will adapt. What will humans do when robots can perform tasks like driving, cleaning, or even teaching? It’s a problem that requires long-term thinking, especially since automation leads to greater wealth concentration in the hands of a few."

"Right now, AI is still just a very advanced tool. It doesn’t have the ability to make its own decisions or have its own goals like humans do. To be human, you need to have agency, a purpose, and a soul. AI hasn’t reached that level yet. Maybe in the far future, it’s possible, but it’s still a long way off—probably around 50 years."

"I am honoured and delighted to join Oxford, which has unparalleled expertise in AI and related fields and amazing students."

"I am looking forward to forging new collaborations and synergies within the Department and beyond that would allow us to develop the next generation."

"It will be possible to overcome the lack of experimental data with simulation and it’s an interesting question how to combine simulated data."

"It is very expensive to obtain experimental data."

"Learning methods that solve real-world problems and at the same time have the trust of domain experts and the broader public."

"What I would like to do is to take a step back and look at the next generation of data sources where the consumer of the data will not be a human but a machine."

"One example is Recursion that scaled-up cell-painting technologies, allowing to image hundreds of millions of cells and see what happens to the cells. *When you perturb them either chemically or genetically."

"If we say that the data does not necessarily need to be viewed by human scientists, we can come up with completely new experimental data sources."

"The range and diversity of problems in biology is significantly bigger than in language."

"We don’t yet have anything of comparable scale in biology, and probably the main limitation is the amount of data we have."

"It could be that in some applications we don’t necessarily need the kind of scale we find in ChatGPT."

"How well it can generalize across tasks."

"In this sense we are probably still far away from general intelligence and this is one of the reasons why I personally don’t like the term artificial intelligence."

"In large language models such as ChatGPT, the key to their success was the scale, being able to create very large models that can be trained on huge amounts of data."

"We don’t really understand and agree on what intelligence is."

"François Chollet posits that intelligence is not about how well a specialized model performs, but how good it is in learning new things, or in other words,"

"Biotech and pharma companies try to do it and successfully in many cases."

"I think there is some broadness to the definition of what counts as a foundation model, and more generally, artificial intelligence."

"If someone was to ask us to describe our , we might be hard pressed to find anything to talk about that we might say was at all interesting, because daily life suggests routine, and routine by definition involves things that are not out of the ordinary."

"are marshalled in the service of satire against powerful individuals and s, to degrade and belittle them; excreta are not on the whole used as images of celebration and festivity ..."

"... most sociologists who would want to talk about wine for one reason or another probably have some personal interest in it. Why spend so much time building up a for something you cannot stand, or which—if you are an alcohol-abstainer—you are opposed to on moral or some other grounds? After all, if you publicly present yourself as an analyst of wine, you are publicly associating yourself with it, and audiences will read you as linked to wine in some way. (The hostile reception to wine talks I have given, by students who seemed to be of a religious fundamentalist persuasion, is a case in point.)"

"I'm going to take you through this, looking at the way history of the way math has impacted our civilization. ...I'll try and take you right up to where we are at the moment, and beyond."

"Math is also developed by curiosity, and just pure abstract reasoning as well, so there's lots of ways it works."

"Where did math come from? ...Early people counted on their fingers, and numbers basically came from that. ...There's no other reason for choosing ten. Ten isn't a great number for a base. Very few numbers divide into it. If we had 12 fingers we would have been better..."

"So film, entertainment, graphic design, the retail industry uses lots of mathematicians. When you go and buy something... sadly, they're collecting data... If you go to Amazon and... buy a book, it will say, "People who bought this book also were interested in this!" ...[T]here's a mathematical algorithm that's doing that. ...It's great news for young people, because... there's vast numbers of jobs, if you stick with the maths."

"One of my other talks... is about the math in The Lord of the Rings and all the maths that was used for that, because... they used lots of mathematicians there."

"The way you... deal with... a problem from industry is you take all the math that you know... and you try and solve the problems with it. ...[A]fter a while you find that you've run out of math. The math that you've learned isn't enough to... solve the problem. So...you have to... invent new math, and... that new math can be... abstracted and turned into other stuff, and then... used to solve new problems, and... you look at those new problems and... find that you need new math from that... and so it... cascades, with problems generating maths, generating problems, and so on. ...[I]t's a really good virtuous circle, and this is... how math is developed over many years."

"The ians were a little... more advanced. They used the knuckles as well. They counted not only in 10s but in 60s... and that's why we have 60 seconds in a minute, 60 minutes in an hour, and 360 degrees in a circle."

"The way maths is used... has... changed enormously, essentially in my own lifetime. ...The whole thing has changed remarkably, largely because of the develoopment of computers."

"Who was the most famous female mathematician? ...Emmy Noether, [was an] excellent... fantastic mathematician, but if I went into the street, who would know Emmy Noether? ...Even more famous than Marie Curie. Films have been made about this woman. Ada Lovelace... famous, but not as famous as this one. I've seen films, books have been written about her. Hugely famous, most children would know her name. I'm going to put her picture up and it's going to surprise you. ...Florence Nightingale's an incredibly famous woman because... she basically founded modern nursing. ...The story ...she was sent to Crimea and... set up hospitals... which saved huge number of lives, and when she went back to England she developed modern nursing and her practice... are used all over the world, and everyone thinks she's a nurse, but... she was a . She was one of the first members of the and was a really good statistician... [T]he way she cured people wasn't so much through medical care. It's through the... more modern approach, which was to try to work out what was causing people to be ill. ...[S]he gathered loads and loads of data on this and... produced graphs of this data... essentially to convey what she was doing to politicians, because politicians then and sadly now, don't know what numbers are... [S]o she did this through graphical information and she developed... rose diagrams which are very like pie charts... [S]o she not only developed ... she also developed graphical presentation of data, which is universal, and she's incredibly famous, but noone knows she was a mathematician. ...The Royal Statistical Society ...building is called the Nightingale building, after her."

"So... [who needs math?] Thirty years ago [traditional industrial users] typically using mathematics... [were] telecommunications, the aircraft industry [aerospace], power generation, oil, iron and steel, weather forecasting... a big user since the 1920s, security-code breaking... and of course, finance."

"Faraday... wasn't a mathematician and so he relied on other people to do his math... and Maxwell... took Faraday's experimentally derived results, and... turned them into mathematical equations.{{center|1=\nabla \times \mathbf{E} = -\frac{\partial \mathbf{B}}{\partial t} - \mathbf{M}, \quad \nabla \times \mathbf{H} = -\frac{\partial \mathbf{D}}{\partial t} + \mathbf{J}, \nabla \cdot \mathbf{D} = \rho, \quad \nabla \cdot \mathbf{B} = 0.}} ...and these are called Maxwell's equations, and if you go to Edinburgh and you see his statue, on the base of the statue you will see these equations... which link electricity \mathbf{E} with \mathbf{B} and \mathbf{M}, which are magnetism, and \mathbf{J} is current, and \rho is charge, and these are... vector operations, and that's a derivative. ...Maxwell ...took those equations and looked for solutions, and... discovered that there were solutions... where you have an electric wave and a magnetic wave... paired... and traveling together, and he worked out the speed of those waves... exactly the speed of light. ...[I]n those equations he unified electricity, magnetism and optics all in one setup."

"But then he did something which mathematicians can do... [i.e.,] what-if experiments. You can say... what if these equations have other solutions, and he found... waves with the same speed as light, but a different and than light... and we now call them radio waves. ...Maxwell discovered radio by pure mathematics alone. It was later... that... Hertz found them experimentally, and... later... Marconi and others took the theory and turned it into practical means of communication."

"I'm going to show a picture of a mathematician... that has changed your life profoundly more than anyone I could possibly think of. ...Whilst I'm a great admirer of Washington and Franklin and... all these wonderful people, I reckon this guy's changed your life even more... This is Maxwell, but... most audiences haven't a clue who this is."

"If there wasn't air around me, I'd die very very quickly... and math is like that for technology. Take the math away, the technology fails, but just like the air around us it's invisible, and lots of people don't know it's there."