The new Find X9 Pro has a built-in 200-megapixel telephoto lens, but you can get even closer with a hefty Hasselblad zoom lens. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. For several years, the top Chinese smartphone brands have been duking it out for photography dominance . Even though year-over-year changes are often minuscule, these companies try to one-up one another.

Proximal Policy Optimization (PPO)-based reinforcement learning from human feedback (RLHF) is a widely adopted paradigm for aligning large language models (LLMs) with human preferences. However, its training pipeline suffers from substantial inefficiencies due to sequential multi-model dependencies (e.g., reward model depends on actor outputs) and long-tail response lengths, where a few long responses straggle the stage completion. We present OPPO, a novel, lightweight, and model-agnostic PPO-based RLHF framework that improves training efficiency by overlapping pipeline execution. OPPO introduces two novel techniques: (1) Intra-step overlap, which streams upstream model outputs (e.g., actor model) in right-sized chunks, enabling the downstream model (e.g., reward) to begin prefill while the upstream continues decoding; and (2) Inter-step overlap, which adaptively overcommits a few prompts and defers long generations to future steps, mitigating tail latency without discarding partial work. OPPO integrates easily with existing PPO implementations with a few lines of code change. Extensive evaluations show that OPPO accelerates PPO-based RLHF training by $1.8 \times-2.8 \times$ and improves GPU utilization by $1.4 \times-2.1 \times$ without compromising training convergence.

There was a time when smartphone makers rushed to quad-camera claims, most of which did so by throwing in a mediocre fourth camera -- usually for macro shots, if not a monochrome filter or just a depth sensor. Nowadays, though, we are blessed with legit quad "main" cameras on some flagship phones, so brands need to be more creative to further differentiate themselves. In Oppo's case, it decided to feature not just one, but two periscope telephoto cameras on its new Snapdragon 8 Gen 3-powered Find X7 Ultra, as a leap from the triple camera system on the previous model. The Find X7 Ultra's "HyperTone Camera System" features the same 50-megapixel resolution across all four rear Hasselblad cameras, thanks to their relatively large sensors compared to the competition, according to Oppo. The main imager packs Sony's second-gen 1-inch sensor, the LYT-900, which is more efficient in terms of power consumption and thermal performance. This is complemented by an f/1.8 aperture, OIS (optical image stabilization), a 23mm focal length and a 50-percent reduction in lens reflection.

This study focuses on the topic of offline preference-based reinforcement learning (PbRL), a variant of conventional reinforcement learning that dispenses with the need for online interaction or specification of reward functions. Instead, the agent is provided with fixed offline trajectories and human preferences between pairs of trajectories to extract the dynamics and task information, respectively. Since the dynamics and task information are orthogonal, a naive approach would involve using preference-based reward learning followed by an off-the-shelf offline RL algorithm. However, this requires the separate learning of a scalar reward function, which is assumed to be an information bottleneck of the learning process. To address this issue, we propose the offline preference-guided policy optimization (OPPO) paradigm, which models offline trajectories and preferences in a one-step process, eliminating the need for separately learning a reward function. OPPO achieves this by introducing an offline hindsight information matching objective for optimizing a contextual policy and a preference modeling objective for finding the optimal context. OPPO further integrates a well-performing decision policy by optimizing the two objectives iteratively. Our empirical results demonstrate that OPPO effectively models offline preferences and outperforms prior competing baselines, including offline RL algorithms performed over either true or pseudo reward function specifications. Our code is available on the project website: https://sites.google.com/view/oppo-icml-2023 .

Google Bard is the company's answer to ChatGPT: an AI chatbot using LaMDA, the company's in-development language model. We've been testing it, and what's immediately clear are all the company's warnings, whether it's the experiment label or the regular reminders that Bard "will not always get it right." Even the example entries, when you boot up Bard, include what the chatbot can't do. The big difference between Google and Bing's integration is the alternative responses that Bard throws up alongside the conversation. You can click the dropdown arrow next to "View other drafts" at the top left of each chat bubble to see some other suggestions.

Seven papers submitted by OPPO were selected for presentation at the 2022 Computer Vision and Pattern Recognition Conference, breaking a new record for the company. The selected papers cover OPPO's various R&D breakthroughs in a range of artificial intelligence disciplines OPPO received a total of eight prizes in the CVPR challenges, including three first-place, one second place, and four third place prizes SHENZHEN, CHINA - Media OutReach - 23 June 2022 - The annual Computer Vision and Pattern Recognition Conference (CVPR) came to an end in New Orleans today, with globally leading technology company OPPO successfully having seven of its submitted papers selected for the conference, putting it among the most successful technology companies at the event. OPPO also placed in eight of the widely watched competition events at the conference, taking home three first place, one second place, and four third place prizes. As deep learning technology has developed over the years, artificial intelligence has shifted from perceptual intelligence to cognitive intelligence. In addition to being able to'see' or'hear' like humans, modern AI technology is now able to demonstrate a similar level of cognitive ability to humans too.

Still not sold on foldable smartphones? But companies continue their efforts to make them happen, with Oppo the latest to reveal its first take on a foldable flagship. It has a different screen ratio to devices from Samsung and the rest, resulting in a more horizontal (possibly more useful) touchscreen. Engadget Chinese Editor-in-Chief Richard Lai is testing one out -- expect to hear our full verdict soon. The US government is adding eight Chinese companies, including drone manufacturer DJI, to an investment blocklist for alleged involvement in the surveillance of Uyghur Muslims.

The 2021 Game Awards kicked off last night, mixing the year's winners (It Takes Two, Deathloop, Kena and several more) with fresh game trailers and bona fide compelling new releases incoming, including Alan Wake 2 . We also got a release date for Final Fantasy VII Remake on PC, new Star Wars, Dune and Star Trek games and several (ten, actually) Lady Gaga hits coming to Beat Saber. There may be something for every gamer. 'Among Us' is heading to VR with help from the'I Expect You To Die' team'Slitterhead' is a new horror game from the creator of Silent Hill The'Cuphead' DLC will finally arrive on June 30th Oppo has teased its first foldable smartphone nearly three years after it unveiled a prototype device. The Find N looks like a device along the lines of Samsung's Galaxy Fold lineup, created after "four years of intense R&D and six generations of prototypes."

Global technology company OPPO announced that the OPPO Research Institute has officially released its first 6G white paper - "6G AI-Cube Intelligent Networking". As one of the global and MENA region's telecommunications industry's first in-depth reports on how artificial intelligence (AI) can empower 6G network architecture, the white paper proposes a more detailed vision for the design of next-generation communication networks. OPPO has established a pre-research team to conduct preliminary research on 6G service and technology requirements, key technologies, and system features. The global smartphone leader believes that 6G will reshape the way people interact with AI, as it is utilised to serve the public through a myriad of applications. In June 2021, UAE telecoms provider Etisalat announced plans for 6G – stating that the network is expected to be even faster and support applications such as augmented and virtual reality, as well as AI infrastructure.

While policy-based reinforcement learning (RL) achieves tremendous successes in practice, it is significantly less understood in theory, especially compared with value-based RL. In particular, it remains elusive how to design a provably efficient policy optimization algorithm that incorporates exploration. To bridge such a gap, this paper proposes an Optimistic variant of the Proximal Policy Optimization algorithm (OPPO), which follows an "optimistic version" of the policy gradient direction. This paper proves that, in the problem of episodic Markov decision process with linear function approximation, unknown transition, and adversarial reward with full-information feedback, OPPO achieves O (\sqrt{d 3 H 3 T}) regret. Here d is the feature dimension, H is the episode horizon, and T is the total number of steps.