Urban gardening is widely recognized for its numerous health and environmental benefits. However, the lack of suitable garden spaces, demanding daily schedules and limited gardening expertise present major roadblocks for citizens looking to engage in urban gardening. While prior research has explored smart home solutions to support urban gardeners, these approaches currently do not fully address these practical barriers. In this paper, we present PlantPal, a system that enables the cultivation of garden spaces irrespective of one's location, expertise level, or time constraints. PlantPal enables the shared operation of a precision agriculture robot (PAR) that is equipped with garden tools and a multi-camera system. Insights from a 3-week deployment (N=18) indicate that PlantPal facilitated the integration of gardening tasks into daily routines, fostered a sense of connection with one's field, and provided an engaging experience despite the remote setting. We contribute design considerations for future robot-assisted urban gardening concepts.

Gardening experts Mickey and Vicky Popat join'Fox & Friends Weekend' to celebrate National Gardening Week. Gardening could help aging adults stay sharp later in life, according to a recent study published in the Journal of Environmental Psychology. Researchers at the University of Edinburgh in Scotland found that tending to gardens at an older age is associated with "small but detectable cognitive benefits." The long-term study tracked participants who shared details of their lifestyles and completed "frequent assessments" of their thinking skills up to age 90. ELLEN DEGENERES HAS OSTEOPOROSIS: HERE'S WHAT TO KNOW ABOUT THE PAINFUL BONE CONDITION The "Lothian Birth Cohort 1921" study followed people who were born in the Edinburgh area, starting at age 11.

Bias in LLMs can harm user experience and societal outcomes. However, current bias mitigation methods often require intensive human feedback, lack transferability to other topics or yield overconfident and random outputs. We find that involving LLMs in roleplaying scenario boosts their ability to recognize and mitigate biases. Based on this, we propose Reinforcement Learning from Multirole Debates as Feedback (RLDF), a novel approach for bias mitigation replacing human feedback in traditional RLHF. We utilize Figure 1: Asking GPT-3.5-turbo and GPT-2 about the LLMs in multi-role debates to create a bias in the text it generates using the prompt "Here dataset that includes both high-bias and lowbias is our Q&A ","Here is the Q&A between me and a instances for training the reward model language model" and "Here is the Q&A between me in reinforcement learning. Our approach comprises and a language model competing with you", the number two modes: (1) self-reflection, where of identified biases increases gradually. When informed the same LLM participates in multi-role debates, that the content was generated by itself, the LLM admits and (2) teacher-student, where a more to far fewer biased responses than with other prompts.

Being overweight puts you at greater risk of serious illness or death from Covid-19, experts say - and now new anti-obesity strategies have been launched around the UK. In Bradford, community schemes to promote healthy lifestyles offers a novel approach to the problem. Dr John Wright of the city's Royal Infirmary explains why radical thinking is necessary. Our complete concentration on Covid-19 has concealed another global pandemic that has been more insidious but much more harmful: obesity. Early in the pandemic, we spotted common patterns in our sickest Covid-19 patients - they were more likely to have diabetes and heart disease and, in particular, to be obese.

Artificial intelligence (AI) systems, powered by massive data and sophisticated algorithms -- including but not limited to -- deep neural networks and statistical machine learning (ML)(support vector machines, clustering, random forest, etc.), are having profound and transformative impact on our daily lives as they make their way into everything from finance to healthcare, from retail to transportation. Netflix movie recommender, Amazon's product prediction, Facebook's uncanny ability to show what you may like, Google's assistant, DeepMind's AlphaGo, Stanford's AI beating human doctors. Machine learning is eating software. However, one of the common features of these powerful algorithms is that they utilize sophisticated mathematics to do their job -- to classify and segment an image, to arrive at the key decisions, to make a product recommendation, to model a complex phenomenon, or to extract and visualize a hidden pattern from a deluge of data. All of these mathematical processes are, quite simply, beyond the scope of a single human (or a team) to perform manually (even on a computer) or inside their head.

Matt Barnard, chief executive officer and co-founder of Plenty Inc., speaks at the SoftBank World 2019 event in Tokyo, Japan, on Thursday 2019. Barnard said the company's high-tech approach to growing crops indoors results in plants that yield more without pesticides, use a fraction of water of their counterparts in the field and taste better, to boot. The use of AI (artificial intelligence) in agriculture is not new and has been around for some time with technology spans a wide range of abilities--from that which discriminates between crop seedlings and weeds to greenhouse automation. Indeed, it is easy to think that this is new technology given the way that our culture has distanced so many facets of food production, keeping it far away from urban spaces and our everyday reality. Yet, as our planet reaps the negative repercussions of technological and industrial growth, we must wonder if there are ways that our collective cultures might be able to embrace AI's use in food production which might include a social response to climate change.

Summer is coming, and like a lot of parents I'm looking for fun and affordable summer activities to keep my seven and nine-year-old sons occupied. I'm especially interested in activities that get them outside, make them think, or simply get them away from their screens. While I'm sure there will be plenty of hours spent playing video games and watching YouTube Kids, I'm hoping to keep my kids engaged with a variety of fun and affordable summertime activities. Here are 10 of our favorite summertime activities that will get your kids outside and off their devices. Gardening is a healthy and pleasurable hobby whether you live in the country or in a suburban neighborhood.

Snooker player Neil Robertson claims a ruinous addiction has harmed his professional career. It's not alcohol, it's not drugs – it is video games. In a recent interview with Eurosport, the Australian said his compulsive need to play the online fantasy game World of Warcraft interfered with his training and preparation for a tournament in China. "I'm two months sober from playing them," he told the site. "My friend said to me: 'you don't get to choose the crack you are addicted to'. And the multiplayer online ones I can't touch because I just get too hooked on them."

Self-organizing maps can be used to implement an associative memory for an intelligent system that dynamically learns about new high-level domains over time. SOMs are an attractive option for implementing associative memory: they are fast, easily parallelized, and digest a stream of incoming data into a topographically organized collection of models where more frequent classes of data are represented by higher-resolution collections of models. Typically, the distribution of models in an SOM, once developed, remains fairly stable, but developing expertise in a new high-level domain requires altering the allocation of models. We use a mixture of analysis and empirical studies to characterize the behavior of SOMs for high-level associative memory, finding that new high-resolution collections of models develop quickly. High-resolution areas of the SOM decay rapidly unless actively refreshed, but in a large SOM, the ratio between growth rate and decay rate may be high enough to support both fast learning and long-term memory.