An In-depth Survey of Large Language Model-based Artificial Intelligence Agents

Due to the powerful capabilities demonstrated by large language model (LLM), there has been a recent surge in efforts to integrate them with AI agents to enhance their performance. In this paper, we have explored the core differences and characteristics between LLM-based AI agents and traditional AI agents. Specifically, we first compare the fundamental characteristics of these two types of agents, clarifying the significant advantages of LLM-based agents in handling natural language, knowledge storage, and reasoning capabilities. Subsequently, we conducted an in-depth analysis of the key components of AI agents, including planning, memory, and tool use. Particularly, for the crucial component of memory, this paper introduced an innovative classification scheme, not only departing from traditional classification methods but also providing a fresh perspective on the design of an AI agent's memory system. We firmly believe that in-depth research and understanding of these core components will lay a solid foundation for the future advancement of AI agent technology. At the end of the paper, we provide directional suggestions for further research in this field, with the hope of offering valuable insights to scholars and researchers in the field

Collaborative Real-Time Interactive Billboard Networks

Online advertising and marketing nowadays has become more and more popular, and there are increasing number of companies that comes into the battle of this market. As everyone can see, advertisement is dispensable part for almost every website. When we are browsing the websites, we have access to various advertisements. Some of them are even based on our activities in the browser so that the advertisements can be more relevant to us, and consequently increase the impressions and click on the advertisements. To make this kind of advertising more efficient and profitable not only benefits the advertiser, but also helps websites and advertising technology vendors to grow. There are many technology companies that provides the platform for websites and advertisers, where they websites can offer their advertisement spots and advertisers are able to pick their favorite places to render the advertisements. Since the process is very wide open on the Internet, it can involve huge amount of data which could be over million or even billion. Also most of advertising technology companies have real-time bidding system which really helps to activate the whole market and maximize the profit of advertisers, websites and themselves. However, as the online advertising roaring up, it seems the billboard market is left behind. Compared to websites advertisement spots, billboard is much more physical and harder to operate. billboard owners are using different players and CMS(content manage- ment systems) to operate their billboards. Those CMS may be costly, for which billboard owners may be not willing to replace their existing system with other new methods. So it will be difficult and complicated to integrate different individual billboard operating networks together. But good news is people are choosing digital LED billboard over other kinds of billboards because it is easier to control and can provide more options to advertis- ers in terms of the type of advertisements. Therefore, i may be a good time to incorporate a system that helps to involve all the digital billboards under the hood and make outdoor billboard advertising as efficient as online advertising. Firstly, in order to contain billboards as many as possible, we need one single place for billboard owners to show and describe their billboards, and meanwhile advertisers can are able to see those information and make their decisions based on the locations and the prices. Secondly, to be able to distribute the advertisement contents to the billboards, a hardware is required to install in the billboard so that it can communicate with the server and grab the content and the schedule. Thirdly, to increase the compatibility between different existing billboard management systems that billboard owners are using themselves, the hardware has to be an add-on device which does not interfere the original work flows. Finally, the system should allow convenient interaction between advertisements and consumers so that the consumers can access the resources of the products or services which are being advertised, just like an end user clicking an advertisement on the Internet. Based on these four perspectives, a collaborative real-time interactive system for billboards is introduced and discussed

AMER: Automatic Behavior Modeling and Interaction Exploration in Recommender System

User behavior and feature interactions are crucial in deep learning-based recommender systems. There has been a diverse set of behavior modeling and interaction exploration methods in the literature. Nevertheless, the design of task-aware recommender systems still requires feature engineering and architecture engineering from domain experts. In this work, we introduce AMER, namely Automatic behavior Modeling and interaction Exploration in Recommender systems with Neural Architecture Search (NAS). The core contributions of AMER include the three-stage search space and the tailored three-step searching pipeline. In the first step, AMER searches for residual blocks that incorporate commonly used operations in the block-wise search space of stage 1 to model sequential patterns in user behavior. In the second step, it progressively investigates useful low-order and high-order feature interactions in the non-sequential interaction space of stage 2. Finally, an aggregation multi-layer perceptron (MLP) with shortcut connection is selected from flexible dimension settings of stage~3 to combine features extracted from the previous steps. For efficient and effective NAS, AMER employs the one-shot random search in all three steps. Further analysis reveals that AMER's search space could cover most of the representative behavior extraction and interaction investigation methods, which demonstrates the universality of our design. The extensive experimental results over various scenarios reveal that AMER could outperform competitive baselines with elaborate feature engineering and architecture engineering, indicating both effectiveness and robustness of the proposed method

Quantitative combination of natural anti-oxidants prevents metabolic syndrome by reducing oxidative stress

AbstractInsulin resistance and abdominal obesity are present in the majority of people with the metabolic syndrome. Antioxidant therapy might be a useful strategy for type 2 diabetes and other insulin-resistant states. The combination of vitamin C (Vc) and vitamin E has synthetic scavenging effect on free radicals and inhibition effect on lipid peroxidation. However, there are few studies about how to define the best combination of more than three anti-oxidants as it is difficult or impossible to test the anti-oxidant effect of the combination of every concentration of each ingredient experimentally. Here we present a math model, which is based on the classical Hill equation to determine the best combination, called Fixed Dose Combination (FDC), of several natural anti-oxidants, including Vc, green tea polyphenols (GTP) and grape seed extract proanthocyanidin (GSEP). Then we investigated the effects of FDC on oxidative stress, blood glucose and serum lipid levels in cultured 3T3-L1 adipocytes, high fat diet (HFD)-fed rats which serve as obesity model, and KK-ay mice as diabetic model. The level of serum malondialdehyde (MDA) in the treated rats was studied and Hematoxylin-Eosin (HE) staining or Oil red slices of liver and adipose tissue in the rats were examined as well. FDC shows excellent antioxidant and anti-glycation activity by attenuating lipid peroxidation. FDC determined in this investigation can become a potential solution to reduce obesity, to improve insulin sensitivity and be beneficial for the treatment of fat and diabetic patients. It is the first time to use the math model to determine the best ratio of three anti-oxidants, which can save much more time and chemical materials than traditional experimental method. This quantitative method represents a potentially new and useful strategy to screen all possible combinations of many natural anti-oxidants, therefore may help develop novel therapeutics with the potential to ameliorate the worldwide metabolic abnormalities