W e use notation Eq.(M.xx) to refer to the equation Eq.(xx) presented in the main paper, and use Eq.(S.xx) Similarly, we use Fig./Section/T able (M.xx) JCL more efficiently exploit these samples. Qi Cai and Y u Wang contributed equally to this work. This work was performed at JD AI Research. Eq.(M.8), we update the queue The ablation experiments are conducted on a subset of ImageNet1K (i.e., ImageNet100) following For the experiments that visualize the distributions of similarities and variances in Section (M.4.5),

Additional Feedback: I think it is too strong to claim that "we also theoretically unveil the certain important mechanisms that govern the behavior of JCL." The main theoretical tool in the proposed method is an application of Jensen's inequality. There is also a section (3.3) that discusses some very basic properties of the the objective. To claim any of this as a significant "theoretical contribution" is too strong in my view. To me, the most interesting aspect of Fig2 is part (b).

This paper achieved a high accept consensus. The paper puts forward a simple core idea, shows it being helpful, and gives analysis/insights that justify how it works. The method beats SOTA in various tasks. However, a bad quality of language and some experimental details missing were reported and I encourage the authors to fix these following the reviewer's recommendations for the final version of the manuscript.

This paper explores useful modifications of the recent development in contrastive learning via novel probabilistic modeling. We derive a particular form of contrastive loss named Joint Contrastive Learning (JCL). JCL implicitly involves the simultaneous learning of an infinite number of query-key pairs, which poses tighter constraints when searching for invariant features. We derive an upper bound on this formulation that allows analytical solutions in an end-to-end training manner. While JCL is practically effective in numerous computer vision applications, we also theoretically unveil the certain mechanisms that govern the behavior of JCL.

We're more distracted than ever. Why remember anything when I can just Google it? Why summon the attention to read a book when I can just scroll through Twitter? Some philosophers believe that ChatGPT and its siblings will further diminish our ability to do the kind of "deep work" needed to spark creativity and breed big ideas. What good are the tools if we begin to rely on them so much that we no longer have the capacity to think bigger?

Our world in the year 2030 may still be miles away from looking like a futuristic set-up, but it will still have enhanced technologies that look like they came out of the realms of science fiction. These developments are also becoming more ubiquitous, with innovators developing Web 3.0 applications using blockchain technologies – meeting the demand of more people wanting greater data ownership through non-fungible tokens (NFTs), cryptocurrencies, as well as the metaverse. Of these developments, the metaverse is the one to watch. Its concept encompasses a fully-immersive, hyper-realistic virtual world that caters to all senses, bridging communities and societies that are physically separated, harnessing collaborations and coming together to have a collective experience in the same digital space. However, this does not stop with just the idea of exploring one common metaverse.

As one of Ireland's leading renewable energy developers and suppliers of green electricity, Energia Group proudly employs numerous scientists working across various fields, from marine biology to data science. Ahead of Science Week, which runs from the 13th to the 20th of November, Energia Group is celebrating the infinite possibilities and the role of science in the energy sector and how that contributes to Ireland's climate goals. Neil Mc Caul, Gregory Balogh and Anchit Bhagat are working together on an innovative artificial intelligence solution that can support energy traders in the decisions they make. Neil Mc Caul, Energy Trading Development Manager with Energia Group has more than 15 years energy trading experience. He has seen first-hand how the rapid increase in digitalization plus the added complexity of many additional energy sources such as solar, increased levels of wind (both onshore & offshore) and battery storage has changed the energy trading industry.

What will video games be like when they can truly harness the power of AI? If the machine learning-powered text adventure AI Dungeon 2 is anything to go by, they'll be open-ended, ludicrously silly, and bags of fun to play. He's harnessed the power of a state-of-the-art, open-source text generation system built by OpenAI and fed it a bunch of texts in the style of Choose Your Own Adventure books. The result is a text adventure where, to modify a cliché, the only limit is the AI's imagination. You can play AI Dungeon 2 for yourself here.

A common measure of machine intelligence is challenging AI to play complex games against humans. The first AI programs tackled checkers and progressed to beat human players at chess, Go and a wide range of multiplayer games. The thinking behind reinforcement learning (RL) is that if a computer can outwit humans by thinking, planning ahead and predicting human behavior, then the machines have the capacity to learn anything. Now, researchers are still studying how computers learn through iteration and trial and error. One of the simplest goal-driven problems that computers were first tasked with was trying to find the right path through a maze.

If you let your imagination run wild in the world of automatic speech recognition (ASR) and natural language understanding (NLU), and you throw in a little fear, uncertainty and doubt (FUD), you can come up with several illegal uses for systems such as Alexa Voice Service, Google Home, Siri, and Cortana that will give you pause. As I have previously written, Alexa is the "killer app" for the Internet of Things (IoT). It is not dangerous, at least not in its present form. But just for fun, let's play pretend in our world of infinite possibilities. Please note: I'm going to use "Alexa" for the wake word in the following examples.