Interviews & Essays

29 Posts

Alon Halevy next to a big computer screen
Interviews & Essays

Alon Halevy: Facebook AI director Alon Halevy envisions your personal data timeline

The important question of how companies and organizations use our data has received a lot of attention in the technology and policy communities. An equally important question that deserves more focus in 2023 is how...
Reza Zadeh photographed during a conference
Interviews & Essays

Reza Zadeh: Generative AI can bring a breakthrough in active learning, says Matroid founder Reza Zadeh

As we enter the new year, there is a growing hope that the recent explosion of generative AI will bring significant progress in active learning. This technique, which enables machine learning systems to generate their own training examples and request them to be labeled...
Portrait photograph of Been Kim
Interviews & Essays

Been Kim: Google Brain researcher Been Kim envisions a scientific approach to interpretability

It’s an exciting time for AI, with fascinating advances in generated media and many other applications, some even in science and medicine. Some folks may dream about what more AI can create and how much bigger models we may engineer.
Douwe Kiela with a l
Interviews & Essays

Douwe Kiela: Natural language processing researcher Douwe Kiela calls for less hype, more caution.

This year we really started to see the mainstreaming of AI. Systems like Stable Diffusion and ChatGPT captured the public imagination to an extent we haven’t seen before in our field.
Yoshua Bengio teaching
Interviews & Essays

Yoshua Bengio: Deep learning pioneer Yoshua Bengio looks forward to neural nets that can reason.

Recent advances in deep learning largely have come by brute force: taking the latest architectures and scaling up compute power, data, and engineering. Do we have the architectures we need, and all that remains is to develop better hardware and datasets so we can keep...
Matt Zeiler
Interviews & Essays

Matt Zeiler: Advance AI for good

There’s a reason why artificial intelligence is sometimes referred to as “software 2.0”: It represents the most significant technological advance in decades. Like any groundbreaking invention, it raises concerns about the future, and much of the media focus is on the threats it brings.
Photograph of Yale Song
Interviews & Essays

Yale Song: Foundation models for vision

Large models pretrained on immense quantities of text have been proven to provide strong foundations for solving specialized language tasks. My biggest hope for AI in 2022 is...
Yoav Shoham
Interviews & Essays

Yoav Shoham: Language models that reason

I believe that natural language processing in 2022 will re-embrace symbolic reasoning, harmonizing it with the statistical operation of modern neural networks. Let me explain what I mean by this.
Chip Huyen
Interviews & Essays

Chip Huyen: AI that adapts to changing conditions

Until recently, big data processing has been dominated by batch systems like MapReduce and Spark, which allow us to periodically process a large amount of data very efficiently.
Alexei Efros
Interviews & Essays

Alexei Efros: Learning from the ground up

Things are really starting to get going in the field of AI. After many years (decades?!) of focusing on algorithms, the AI community is finally ready to accept the central role of data and the high-capacity models that are capable of taking advantage of this data.
Wolfram Burgard
Interviews & Essays

Wolfram Burgard: Train robots in the real world

Robots are tremendously useful machines, and I would like to see them applied to every task where they can do some good. Yet we don’t have enough programmers for all this hardware and all these tasks.
Abeba Birhane
Interviews & Essays

Abeba Birhane: Clean up web datasets

From language to vision models, deep neural networks are marked by improved performance, higher efficiency, and better generalizations. Yet, these systems are also marked by perpetuation of bias and injustice.
Ilya Sutskever
Interviews & Essays

Ilya Sutskever: OpenAI’s co-founder on building multimodal AI models

The past year was the first in which general-purpose models became economically useful. GPT-3, in particular, demonstrated that large language models have surprising linguistic competence and the ability to perform a wide variety of useful tasks.
Harry Shum
Interviews & Essays

Harry Shum: Tsinghua University’s Harry Shum on how AI is changing creativity

In 2021, I envision that the AI community will create more tools to unleash human creativity. AI will help people across the globe to communicate and express emotions and moods in their own unique ways.
Matthew Mattina
Interviews & Essays

Matthew Mattina: Arm research leader explains how TinyML is bringing AI to phones and other edge devices

Look at the tip of a standard #2 pencil. Now, imagine performing over one trillion multiplication operations in the area of that pencil tip every second. This can be accomplished using today’s 7nm semiconductor technology.

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