Automated pose correction remains a significant challenge in AI-driven fitness systems, despite extensive research in activity recognition. This work presents PosePilot, a novel system that integrates pose recognition with real-time personalized corrective feedback, overcoming the limitations of traditional fitness solutions. Using Yoga, a discipline requiring precise spatio-temporal alignment as a case study, we demonstrate PosePilot's ability to analyze complex physical movements. Designed for deployment on edge devices, PosePilot can be extended to various at-home and outdoor exercises. We employ a Vanilla LSTM, allowing the system to capture temporal dependencies for pose recognition. Additionally, a BiLSTM with multi-head Attention enhances the model's ability to process motion contexts, selectively focusing on key limb angles for accurate error detection while maintaining computational efficiency. As part of this work, we introduce a high-quality video dataset used for evaluating our models. Most importantly, PosePilot provides instant corrective feedback at every stage of a movement, ensuring precise posture adjustments throughout the exercise routine. The proposed approach 1) performs automatic human posture recognition, 2) provides personalized posture correction feedback at each instant which is crucial in Yoga, and 3) offers a lightweight and robust posture correction model feasible for deploying on edge devices in real-world environments.

Lenovo has announced new laptops with generative AI features for this year's Mobile World Congress (MWC), including the Yoga Pro 9i Aura edition. Lenovo's Aura edition branding is the result of a partnership with Intel to create a set of "distinct software, hardware and AI features" that make "computing a more personalized, productive, and protected experience." The Yoga Pro 9i Aura edition is powered by the Intel Core Ultra processor and ships with the NVIDIA GeForce RTX 5070 GPU, which is the company's most affordable model in the RTX 50 series. It has a 16-inch 3.2K PureSight Pro display with a double layer of OLED pixels that increases its overall brightness to 1600nits peak, as well as boosts its power efficiency. The display also supports 100 percent sRGB, P3 and Adobe RGB color gamut that provide true-to-life color accuracy.

Lenovo's updated consumer laptop lineup at CES 2024 is (unsurprisingly) focused on AI. The company unveiled an array of Yoga and Ideapad notebooks on Monday in Las Vegas, including new versions of the Yoga Pro 9i and Yoga 9i 2-in-1. The 2024 Yoga Pro 9i and Yoga 9i 2-in-1 still have a military-spec rating (MIL-STD-810H) for durability. Both get a spec bump to the latest Intel Core Ultra "Meteor Lake" processors -- up to Intel Core Ultra 5 / 7/ 9 H Series in the Pro 9i and up to Intel Evo Edition powered by Core Ultra 7 processor in the Yoga 9i 2-in-1. Like practically every other company at CES, Lenovo is touting its new products' AI capabilities.

We introduce YOGA, a deep learning based yet lightweight object detection model that can operate on low-end edge devices while still achieving competitive accuracy. The YOGA architecture consists of a two-phase feature learning pipeline with a cheap linear transformation, which learns feature maps using only half of the convolution filters required by conventional convolutional neural networks. In addition, it performs multi-scale feature fusion in its neck using an attention mechanism instead of the naive concatenation used by conventional detectors. YOGA is a flexible model that can be easily scaled up or down by several orders of magnitude to fit a broad range of hardware constraints. We evaluate YOGA on COCO-val and COCO-testdev datasets with other over 10 state-of-the-art object detectors. The results show that YOGA strikes the best trade-off between model size and accuracy (up to 22% increase of AP and 23-34% reduction of parameters and FLOPs), making it an ideal choice for deployment in the wild on low-end edge devices. This is further affirmed by our hardware implementation and evaluation on NVIDIA Jetson Nano.

There's no denying that digital transformation has been a major force in business over the past few years. From providing greater customer experience to streamlining processes, digital transformation has changed the way we do business in the modern world. But what exactly is digital transformation, and why is it important for business? In short, digital transformation is the process of leveraging technology to improve customer experience, automate processes, and create new business opportunities. It involves digitalizing business operations, such as introducing cloud storage, automation, and analytics.

Imagine a day in the future when you wake up to an alarm buzz of a smart assistant. Well, you may wonder is that not something available already in the present day? That's right, but what if the smart assistant also transforms itself into a'smart fitness trainer' that can interact and guide on a personalised workout routine depending on your wellness goals, prevailing health conditions, and recovery needed based on previous night's sleep pattern? Yes, in future, those smart assistants could become one's true'wellness' companion to help individuals keep up with their habits and maintain healthy lifestyle – be it Mindfulness, Exercise, Diet, and Sleep (MEDS). That day in the future is not too far away.

Social media platforms provide convenient means for users to participate in multiple online activities on various contents and create fast widespread interactions. However, this rapidly growing access has also increased the diverse information, and characterizing user types to understand people's lifestyle decisions shared in social media is challenging. In this paper, we propose a weakly supervised graph embedding based framework for understanding user types. We evaluate the user embedding learned using weak supervision over well-being related tweets from Twitter, focusing on 'Yoga', 'Keto diet'. Experiments on real-world datasets demonstrate that the proposed framework outperforms the baselines for detecting user types. Finally, we illustrate data analysis on different types of users (e.g., practitioner vs. promotional) from our dataset. While we focus on lifestyle-related tweets (i.e., yoga, keto), our method for constructing user representation readily generalizes to other domains.

VARANASI: A student of the Indian Institute of Technology, Banaras Hindu University (IIT-BHU) claims to have developed the first version of an artificial intelligence-based yoga platform through Multiplayer Yoga Gameplay (MPYG) that will teach how to do yoga in the right manner. Vidyabhushan, a third-year chemical engineering student, has developed the platform with mentorship, funding from NASSCOM Foundation, Cisco Thingcubator and technical support from NCL-IIT BHU Incubation Centre. "MPYG is an innovation in the field of Yoga. It is an artificial intelligence and augmented reality-based community yoga platform. It will make people choose yoga keeping in mind the health-related factors and is designed with the aim of getting people to do yoga in the right way," said Vidyabhushan.

Multiview representation learning of data can help construct coherent and contextualized users' representations on social media. This paper suggests a joint embedding model, incorporating users' social and textual information to learn contextualized user representations used for understanding their lifestyle choices. We apply our model to tweets related to two lifestyle activities, `Yoga' and `Keto diet' and use it to analyze users' activity type and motivation. We explain the data collection and annotation process in detail and provide an in-depth analysis of users from different classes based on their Twitter content. Our experiments show that our model results in performance improvements in both domains.

The new ThinkPads are here, and they're packed with exciting new features. Fresh for the all-virtual CES 2021 exhibit, Lenovo has dropped four new models: the 9th gen X1 Carbon, the 6th gen X1 Yoga, and the brand new X1 Titanium Yoga and X1 Detachable. We're especially curious about the X1 Detachable, which is basically Lenovo's version of the Microsoft Surface Book 3--a laptop with a completely detachable screen that turns into a tablet. Unlike a tablet with a keyboard folio, the Surface Book 3 feels like a classic clamshell laptop when the display and keyboard are connected, and we expect the X1 Detachable will have a similar feel. The ThinkPad X12 Detachable could be a long-due rival for the Microsoft Surface Book 3. This is one of the most interesting releases of CES.