Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. However, their performance in specific professional domains such as medicine, especially within the open-source community, remains suboptimal due to the complexity of medical knowledge. In this paper, we propose CareBot, a bilingual medical LLM, which leverages a comprehensive approach integrating continuous pre-training (CPT), supervised fine-tuning (SFT), and reinforcement learning with human feedback (RLHF). Our novel two-stage CPT method, comprising Stable CPT and Boost CPT, effectively bridges the gap between general and domain-specific data, facilitating a smooth transition from pre-training to fine-tuning and enhancing domain knowledge progressively. We also introduce DataRater, a model designed to assess data quality during CPT, ensuring that the training data is both accurate and relevant. For SFT, we develope a large and diverse bilingual dataset, along with ConFilter, a metric to enhance multi-turn dialogue quality, which is crucial to improving the model's ability to handle more complex dialogues. The combination of high-quality data sources and innovative techniques significantly improves CareBot's performance across a range of medical applications. Our rigorous evaluations on Chinese and English benchmarks confirm CareBot's effectiveness in medical consultation and education. These advancements not only address current limitations in medical LLMs but also set a new standard for developing effective and reliable open-source models in the medical domain. We will open-source the datasets and models later, contributing valuable resources to the research community.

Corp. (PINKSHEETS: GCKO) -- announced today that one of their care giver participants has "looked in" on her mother while shopping. Her testimonial characterizes some of the benefits she is realizing from the CareBot and its remote monitoring and telepresence capabilities. GeckoSystems is a dynamic leader in the emerging Mobile Service Robot (MSR) industry revolutionizing their development and usage with their "Mobile Robot Solutions for Safety, Security, and Service ". "In the past I have not been able to'look in' on my elderly mother at home alone while I was out shopping. There was always a concern if she was okay during my absence, especially if she had some new health issue. Today, for the first time, I was able to watch her while grocery shopping at Ingles with the help of her CareBot. "I took my Dell netbook with me.

Corp. (PINKSHEETS: GCKO) -- -- announced today that they have further cost reduced their robot controller board, the GeckoSPIO, while improving ease of manufacturability and maintaining robust functionality. GeckoSystems is a dynamic leader in the emerging mobile robotics industry revolutionizing their development and usage with "Mobile Robot Solutions for Safety, Security, and Service ". "The GeckoSPIO is the critical interface between the robot's physical platform and higher AI functions. This interface provides a level of abstraction for the commands sent to, and the data sent from, the robot platform. The abstraction and hierarchal architecture the GeckoSPIO provides simplifies interacting with the platform and the real world for the high-level software, along with enabling a wide array of sensor fusion techniques. We are pleased that one of our recently hired electrical engineers has made these improvements," stated Mark Peele, Vice President, R&D, GeckoSystems.

Research shows that doctors who offer empathic and positive messages can reduce a patient's pain, improve their recovery after surgery, and lower the amount of morphine they need. But it doesn't mean that telling a patient something simple, such as "this drug will make you feel better," will have an effect. Positive messages are usually repeated, definite, specific, and personal. They should also be communicated by an authority figure who shows empathy (see graphic below). While our study does not identify what the most effective components of a positive message are (the sample was too small), the results imply that, for example, a positive message that is not specific or personalized and is delivered by a doctor perceived to lack authority and empathy, will not have the desired effect.

We are not used to the idea of machines making ethical decisions, but the day when they will routinely do this - by themselves - is fast approaching. So how, asks the BBC's David Edmonds, will we teach them to do the right thing? The car arrives at your home bang on schedule at 8am to take you to work. You climb into the back seat and remove your electronic reading device from your briefcase to scan the news. There has never been trouble on the journey before: there's usually little congestion.

We are not used to the idea of machines making ethical decisions, but the day when they will routinely do this - by themselves - is fast approaching. So how, asks the BBC's David Edmonds, will we teach them to do the right thing? The car arrives at your home bang on schedule at 8am to take you to work. You climb into the back seat and remove your electronic reading device from your briefcase to scan the news. There has never been trouble on the journey before: there's usually little congestion.

People in the FinTech space like to say that FinTech will disrupt financial services beyond recognition, causing mass disruption of its delivery to consumers. Artificial intelligence ("AI") will disrupt all financial services, indeed all of our society. Technically, AI is intelligence created by machines or software, sometimes called machine learning and sometimes confused with robotics. Robotics is just the robotization of something – if is has the capability to learn, then robotics can be AI. The artificial intelligence and robotics market combined was worth US$10.7 billion in 2014 and is expected to be worth US$153 billion by 2020, and to have a disruptive impact of between US$14 to US$33 trillion.

If you are interested in reaching customers that you can't get to now, in offering user experiences that go beyond the rigid orchestration of the point and click paradigm, in providing just the right data that someone needs, it may be time to consider creating a chatbot. When I ran across the description of Colin Megill's course for O'Reilly Media about how to build your own chatbot (which is starting on July 13), I thought of Eliza, one of the pioneering chatbots that did a serviceable job of parsing sentences and tossing them back to you. Eliza made it seem like you were having a conversation if you got lucky. If you said something it couldn't handle, the conversation quickly got dull or non-sensical. The world has grown up.

Douglas Hines started out with what sounded like a nice idea. In the early 2000s, the former Bell Labs engineer was busy caring for his elderly father and building his own technology business. That's when he first came up with the idea for a companion robot: a machine that could look after his dad and keep him in touch with the outside world via webcam. Hines started working on a prototype, but ran into trouble finding financial and legal support for the project. So he gave up, and instead turned his attentions to Roxxxy, a life-size sexbot dressed in filmy black lingerie ("always turned on and ready to talk or play!").

By 2020, a quarter of Europeans will be over 60. In their silver age, many would like to stay in their homes and will require care from family or social workers. Unfortunately, the number of caregivers is diminishing year-after-year due to shifting demographics and an increase in working families. This leads to a'care deficit' that poses a major challenge to most European societies. And today's social workers are often hard pressed, wishing they had more time to connect with the people they care for, rather than the minuted dance of tasks that need to be done.