Quotes by famous people, credited to who said them. Your own quotes must not match any of these. More are added all the time. 1,161,747 quotes Who coined it · How we decide
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“There are two sides to it, obviously the course itself, which you can see has been well thought-out in terms of the topics it covers; and then the people and the connections that you make and the learning from each other.”
Josephine Wapakabulo (born 1976) wikiquote, CC BY-SA 4.0 source
“It is important for technology leaders to take the lead and be innovative in the way we communicate to government, because they [government staff] are learning as much as we are”
“I don’t know, but I know I don’t know it all! I believe the entrepreneurship journey is one of discovery. Always stay learning and never think you know everything. Be open to change. Allow growth to happen, and don’t fight it. Find joy and happiness in the little things. And enjoy the work you do!”
Abasi Ene-Obong wikiquote, CC BY-SA 4.0 source
“My project looks both at the context of advanced countries with strong health systems as well as countries where their health systems aren’t as strong. My goal is that my findings will help advance learning, awareness, and advocacy around women’s leadership in health, especially in a time of crisis when effective leadership is needed most.”
Folake Olayinka wikiquote, CC BY-SA 4.0 source
“Learning that is personalized, unique and treats each child as different is key to helping children thrive.”
Evelyn Namara wikiquote, CC BY-SA 4.0 source
“What’s important is finding unique aspects of each child’s learning ability and capitalizing on that to make them better.”
Evelyn Namara wikiquote, CC BY-SA 4.0 source
“That’s why the concept of Blended learning where teaching is done partly using technology and traditional teaching methods works better for young children.”
Evelyn Namara wikiquote, CC BY-SA 4.0 source
“It’s not just about learning technology; it’s about empowering people to use it to solve real problems in their communities”
Olalekan Adeeko wikiquote, CC BY-SA 4.0 source
“I love space, period. Hands down, I think the night sky is one of the most beautiful things in the universe. Learning about space was sort of the thing that I did when I was a kid. And then I found black holes, and life was different.”
Jedidah Isler (born 1982) wikiquote, CC BY-SA 4.0 source
“There is no way to define and measure success or failure. Success for one is failure for another. Being successful or failing are subjective and not always black and white, at least in my opinion. I don’t see failure as an inability to succeed, but a different experience from the ideal. Every experience is a learning one, what is important is to try and not make the same mistake twice”
Radhika Aggarwal wikiquote, CC BY-SA 4.0 source
“To facilitate our implementation we are going to be using the Keras framework. Keras is a high-level API written in Python which runs on-top of popular frameworks such as TensorFlow, Theano, etc. to provide the machine learning practitioner with a layer of abstraction to reduce the inherent complexity of writing NNs.”
Robert Hecht-Nielsen (1947–2019) said by 2019 at the latest wikiquote, CC BY-SA 4.0 source
“Learning to embrace being The Fool is not all-or-nothing. You can ramp into it, starting with smaller bites if that helps you get started.”
Astro Teller (born 1970) wikiquote, CC BY-SA 4.0 source
“And then, after a certain period of time, for me, my barometer was, ‘Is this working for me, right, am I still having fun, am I still developing and learning, and how is that impacting my family life”
“I basically told them, in no uncertain terms, that this was not the way that I thought physics research should be going. And they agreed with me, actually, about the off-the-shelf use of machine learning.”
Jesse Thaler wikiquote, CC BY-SA 4.0 source
“Cosmology is another area with massive amounts of data and massive computational costs to run simulations of the universe. Without something like machine learning, we simply wouldn't be able to tackle those problems.”
Jesse Thaler wikiquote, CC BY-SA 4.0 source
“there is physics for AI, where there are concepts from physics that can help you build better AI tools, even if you aren’t directly studying physical systems. You can build machine learning architectures that have physics-style reasoning embedded and those concepts turn out to be quite powerful.”
Jesse Thaler wikiquote, CC BY-SA 4.0 source
“So while I was a research scientist at Facebook AI Research, I was working on something called reinforcement learning mostly for like robotics, but that’s one of the sort of like essential piece for ChatGPT, like a relationship. And so Aravind and I were, happened to work on the very similar problems.”
Denis Yarats wikiquote, CC BY-SA 4.0 source
“Pinker, ... and myself... have frequently argued... [that] a significant part of a creature’s innate armamentarium consists... of [innate]... mechanisms... that enables learning.”
Gary Marcus (born 1970) wikiquote, CC BY-SA 4.0 source
“The guiding question for the current paper is whether artificially intelligent systems ought... to be endowed with significant... innate machinery, or whether, in virtue of the powerful learning systems... recently... developed, it might suffice for... systems to work in a more bottom up, tabula rasa fashion.”
Gary Marcus (born 1970) wikiquote, CC BY-SA 4.0 source
“... is present in similar forms in... vertebrates, including mammals, birds, reptiles and fish... expressed in corresponding regions of the brain to... humans... [I]n s, changes in expression of the gene in striatal Area X,—a key nucleus of the brain system involved in song learning—appear to relate to alterations in vocal plasticity...”
Gary Marcus (born 1970) wikiquote, CC BY-SA 4.0 source
“Our targets are primarily young people and women living alone especially those in undeveloped communities. In addition, Our mission is simple. We create, enrich the learning communities with the appropriate use of technology.”
Njideka Harry wikiquote, CC BY-SA 4.0 source
“Volunteering worked for me; I believe it is a solution that can tackle the problem of unemployment in Nigeria. By serving and giving your time, it can turn up to learning or earning opportunities.”
Raquel Kasham Daniel wikiquote, CC BY-SA 4.0 source
“Toward this end my group develops and employs various methods in statistical machine learning, natural language processing, information retrieval and data mining---tending toward probabilistic approaches and graphical models. For more information see our current projects and publications.”
Andrew McCallum (1821–1902) said by 1902 at the latest wikiquote, CC BY-SA 4.0 source
“I learned many lessons from my parents: Competence matters, learning is a constant state of mind, respect and honor your elders, and make a difference by investing in organizations. These lessons will guide me throughout the next year.”
Jessica Henderson Daniel wikiquote, CC BY-SA 4.0 source
“The hardware is a collection of about a hundred computers that Garth Gibson (another faculty in our department here), runs as a research project and he lets us use that collection to run NELL....Maybe more interesting than the hardware is how the learning itself works and I could take a few minutes to explain that”
Tom M. Mitchell (born 1951) wikiquote, CC BY-SA 4.0 source
“This hybrid design enables human expertise to help guide and influence machine learning. This technology has been used for drug design, where insights provided by a medicinal chemist on desired properties for a new molecule can complement properties extracted from collected data on different molecules.”
Karen Myers (born 1963) wikiquote, CC BY-SA 4.0 source
“No other theory of natural language processing can better explain or reproduce the results within our territory. You don't need a complex theory of learning, neural nets, or cognitive models to explain how to chat within the limits of A.L.I.C.E.'s 25,000 categories. Our stimulus-response model is as good a theory as any other for these cases, and certainly the simplest.”
Richard Wallace (scientist) wikiquote, CC BY-SA 4.0 source
“I knew that data was always imperfect. It was always partial. It was never the whole story. And so in the early twenty tens, when I saw first machine learning and then we all decided to use the term AI become the next big things following the Alex Net paper, following the recognition that GPUs could effectively supercharge the compute available for neural network training.”
Meredith Whittaker (born 2000) wikiquote, CC BY-SA 4.0 source
“And then I started learning that, in America, they invented a word that means that 26 different countries all of a sudden are one group, and that I was going to belong to that group, and that that group was not terribly well perceived”
Claudia Romo Edelman (born 1971) wikiquote, CC BY-SA 4.0 source
“If you train a neural net using evolutionary learning or predictive coding, you can get non-entangled representations that make it easier for the AI to introspect and understand its own actions.”
Ben Goertzel (born 1966) wikiquote, CC BY-SA 4.0 source
“As of 2016, a rough rule of thumb is that a supervised deep learning algorithm will generally achieve acceptable performance with around 5,000 labeled examples per category, and will match or exceed human performance when trained with a dataset containing at least 10 million labeled examples.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“A representation learning algorithm can discover a good set of features for a simple task in minutes, or for a complex task in hours to months.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“The training algorithm used to adapt the weights of the ADALINE was a special case of an algorithm called stochastic gradient descent. Slightly modified versions of the stochastic gradient descent algorithm remain the dominant training algorithms for deep learning models today.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“It is worth noting that the effort to understand how the brain works on an algorithmic level is alive and well. This endeavor is primarily known as “computational neuroscience” and is a separate field of study from deep learning. It is common for researchers to move back and forth between both fields.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“The field of deep learning is primarily concerned with how to build computer systems that are able to successfully solve tasks requiring intelligence, while the field of computational neuroscience is primarily concerned with building more accurate models of how the brain actually works.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“one of the names that deep learning has gone by is artificial neural networks (ANNs).”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“Several key concepts arose during the connectionism movement of the 1980s that remain central to today’s deep learning. One of these concepts is that of distributed representation (Hinton et al., 1986). This is the idea that each input to a system should be represented by many features, and each feature should be involved in the representation of many possible inputs.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“Working successfully with datasets smaller than this is an important research area, focusing in particular on how we can take advantage of large quantities of unlabeled examples, with unsupervised or semi-supervised learning.”
Ian Goodfellow wikiquote, CC BY-SA 4.0 source
“The field of AI in Education is concerned with development of Artificial Intelligence techniques for the study of human teaching and for the engineering of systems that facilitate human learning.”
Beverly Park Woolf wikiquote, CC BY-SA 4.0 source
“Three research goals have become apparent. The first is to use AI and cognitive science techniques to model experts who problem-solve in a domain, as well as tutors teaching and students learning in that domain.”
Beverly Park Woolf wikiquote, CC BY-SA 4.0 source
“I’m energized by this chance to serve the citizens of Illinois and advance the mission of learning, discovery, engagement and economic development”
Charles Lee Isbell Jr (born 1968) wikiquote, CC BY-SA 4.0 source
“Although I tend to focus on statistical machine learning, my research passion is actually artificial intelligence. I like to build large integrated systems, so I have also tended to spend a great deal of my time doing research on autonomous agents, interactive entertainment, some aspects of HCI, software engineering, and even programming languages.”
Charles Lee Isbell Jr (born 1968) wikiquote, CC BY-SA 4.0 source
“And so then the question is can I somehow take pieces and parts of all these ideas, some human programming, some robot learning in the wild, some kind of search or evolution offline, some inspiration from humans. Can I take all those things and put them together and see if I can find a way to engineer intelligent robots? So that's basically what I'm up to.”
Leslie P. Kaelbling (born 1961) wikiquote, CC BY-SA 4.0 source
“Thanks to both machine-learning models and heterogeneous computing that has accelerated first-principles modeling, we are now able to start asking and answering questions that we could never have addressed before”
Heather Kulik wikiquote, CC BY-SA 4.0 source
“I love learning how to survive off the land.”
Steven Kelly (born 1986) wikiquote, CC BY-SA 4.0 source
“80 percent of adult learning is on their own, so they compare what you are telling them with what they already know.”
Dorothy Kisaka (born 1963) wikiquote, CC BY-SA 4.0 source
“A lot of the progress in machine learning – and this is an unpopular opinion in academia – is driven by an increase in both computing power and data. An analogy is to building a space rocket: You need a huge rocket engine, and you need a lot of fuel.”
Andrew Yan-Tak Ng (born 1976) wikiquote, CC BY-SA 4.0 source
“I would argue that racism, for example, is a feature of machine learning — it’s not a bug.”
Trevor Paglen (born 1974) wikiquote, CC BY-SA 4.0 source
“The advance I’m most excited about right now is a growing, nascent ability to help people understand, using smartphone and wearable sensor data and AI/machine learning, what things in life are most impacting their personal mood, stress, and health.”
Rosalind Picard (born 1962) wikiquote, CC BY-SA 4.0 source
“Reinforcement learning has been a relatively “niche” area of AI since I became interested in it my first year of graduate school. But with recent advances, I became convinced that now was the time to move to the next level and work on problems that are only possible to attack in a commercial setting.”
Peter Stone (professor) wikiquote, CC BY-SA 4.0 source