Nowadays, AI exists everywhere, permeating countless news articles, social media posts, and even the software we use daily. While the concept of AI is not new, generative AI has gained significant attention since the introduction of ChatGPT. Shortly after ChatGPT’s launch, similar generative AI tools emerged, such as Quora’s Poe, Google’s Bard, and Microsoft’s Copilot, leading to the widespread adoption of AI-generated content, videos, code, and more. However, the increasing popularity of AI has also given rise to concerns about the associated risks. Cybercriminals have already discovered methods to extract data from various AI tools, including the utilization of platforms like WormGPT. WormGPT, which can be exploited to generate malicious code. In this blog, we’ll delve into the reasons why generative AI security matters, and then also bring some solutions to help you navigate generative AI security’s risks. Let’s begin! Why Does Generative AI Security Matter Now? AI has a long story, dating back to the 1960s when ELIZA - the first AI chatbot released. However, in recent years, generative AI has gained significant popularity. One major factor contributing to this popularity is the introduction of ChatGPT in late 2022, which has accelerated the development of AI and provided widespread access to this powerful tool. ChatGPT has played a crucial role in democratizing AI by making it more accessible to a broader range of people. By integrating ChatGPT into a search engine front end, it has effectively commoditized AI. As a result, it allows individuals to use it without necessarily understanding the underlying technology.  As various software corporations continue to develop their own AI programs, security teams may face challenges in adapting to these tools. The release of such AI programs, including Microsoft Copilot, which is currently in an early-access phase, can catch security teams off guard, leaving them unaware of how to address the associated risks. Microsoft Copilot offers unique benefits due to its ability to learn about an organization and its LLM (Large Language Model) design. It can join Teams meetings and provide real-time note-taking, assist in triaging emails in Outlook, and even analyze raw data in Excel. But, security teams need to thoroughly understand Copilot’s security model. This understanding will help security teams evaluate the tool’s strengths and weaknesses before its official release. In general, the popularity of generative AI has surged in recent years due to the introduction of ChatGPT, which has made AI more accessible to a wider user. However, as AI tools like Microsoft Copilot continue to emerge, security teams must educate themselves about these technologies to effectively manage the associated risks. Security teams can derive multiple advantages from AI tools like Copilot, beyond its core functionalities. These tools have the potential to enhance various aspects of cybersecurity operations, including bolstering threat detection capabilities and strengthening defense mechanisms. Generative AI offers a range of advantageous applications, including: Blue team defenders: Generative AI tools simplify the process of checking malicious code, detecting vulnerabilities, and summarizing outputs in real-time, enabling businesses to enhance their cybersecurity defenses.…

In the ever-evolving landscape of AI, one standout assistant has emerged to streamline your work and enhance productivity - Poe AI. Over the past year, the surge in the popularity of AI chatbots has been undeniable, but Poe AI distinguishes itself as a comprehensive solution that goes beyond expectations. In this blog, we will delve into what exactly Poe AI is and how it works, which chatbots Poe AI integrates with, and how you can create your own bot on Poe AI. Let’s begin! What Exactly is Poe AI? Poe AI, an acronym for “Platform for Open Exploration”, represents an AI platform developed by Quora. Poe AI facilitates user interaction with a diverse range of AI agents. Poe AI’s launch occurred in December 2022, closely following the public release of ChatGPT. Poe AI opens up a world of interaction and exploration with diverse chatbots driven by expansive language models (LLM) developed by OpenAI and Anthropic. Engage in asking questions, receiving instant responses, and indulging in dynamic conversations with AI chatbots finely tuned for specific tasks. A standout feature of Poe AI is its user-friendly tool that empowers you to craft personalized bots effortlessly. By combining text prompts with an existing bot such as Claude or ChatGPT as the foundation, you can construct your unique bot. This customized creation is then hosted on Poe AI, complete with its distinct URL. In the midst of the escalating presence of AI-powered chatbots in consumer products, Poe AI stands at the forefront of the AI revolution. It simplifies the discovery of distinctive user-generated bots, positioning itself as a catalyst for innovation. Poe AI boasts an array of bots catering to diverse practical needs, from tutoring intricate subjects to aiding in trip planning or engaging in light-hearted conversations. The platform already hosts hundreds of bots, each serving a unique purpose. Accessible through both the web app and mobile platform (Android and iOS), Poe AI ensures a seamless experience, putting the power of AI interaction at your fingertips. What Chatbots Does Poe AI Integrate With? Unlike most other chatbots, Quora’s Poe AI service offers various distinct “personalities” to choose from. They all operate on similar mechanisms but come with different advantages and are designed to perform different tasks. After logging into your Poe AI account, you can discover the available chatbots by navigating to the Explore page. On this page, you’ll find a search bar that allows you to look for specific chatbots or bot developers. Alternatively, utilize the tags located under the search bar to categorize the chatbots into various sections such as Learning, Programming, Sports, Writing, and more! [caption id="attachment_2362" align="aligncenter" width="1024"] Poe AI’s Explorer[/caption] Below is an overview of several official chatbots: ChatGPT: ChatGPT within Poe AI is identical to the ChatGPT version available on the OpenAI website. It is built on the GPT-3.5 language model, slightly more advanced than Sage, but specifically designed for conversational abilities rather than answering questions. It cannot search the internet, and its knowledge is limited to information…

Nowadays, AI in healthcare has emerged as a transformative force, revolutionizing healthcare industries and shaping how we work and interact. The rapid advancements in AI technologies have unleashed a wave of innovation, offering unprecedented opportunities for progress across various domains. Within the next 5 years, 70% of global business leaders believe that AI will significantly impact their industry. Moreover, in 2021, a global survey of healthcare organizations revealed that approximately 20% were at an early stage of adopting AI models, with models in production for less than two years. In this blog, we will give you some knowledge about AI in healthcare and discover the diverse ways in which this technology is poised to reshape the landscape of the healthcare industry. Let’s check it out! What is AI in Healthcare? Healthcare is known as the organized system of medical services and resources. It is designed to promote, maintain, and restore health, prevent disease, and manage illnesses or injuries. AI in healthcare refers to the application of artificial intelligence technologies in the field of healthcare to enhance medical diagnosis, treatment, patient care, and management of healthcare systems.  AI in healthcare involves the use of machine learning algorithms, deep learning, natural language processing (NLP), computer vision, and other AI techniques to analyze, and interpret complex medical data, make predictions, assist in decision-making, and automate various tasks. For those who don’t know, AI in healthcare encompasses a wide range of IT solutions, such as telehealth, custom EMR/EHR, patient engagement software, healthcare information exchange, and so on.  >> Related: Top 6 AI Trends in 2024 You Should Know Some AI Applications in Healthcare Though AI in healthcare is relatively new, it has already shown its potential in various areas of healthcare. These areas include diagnosing patients, and analyzing medical images, providing personalized treatment recommendations, discovering and developing new drugs. So, how does it work when applying AI in healthcare? Let’s explore each of these areas in more detail. 1. Patient Diagnosis and Medical Imaging AI algorithms can analyze medical images such as X-rays, CT scans, and MRIs, assisting radiologists in detecting and diagnosing diseases like cancer, cardiovascular conditions, and neurological disorders. By creating quality images, AI can help improve accuracy, speed up the process, and identify subtle patterns that human eyes might miss. For example, HixClinic - an online appointment booking app leverages the advance of AI to analyze the health level of hair through photos. After analyzing the hair health, HixClinic gives patients advice and warning about their hair’s status. Also, by applying some AI tools, HixClinic can answer the survey about hair improvement, and then increase the customer experience. HixClinic App Thus, AI has the potential to greatly help in the field of healthcare imaging. Just like AMELA, many other healthcare providers and technology companies are actively working on this application because they believe it holds a lot of promise for improving healthcare. 2. Drug Discovery and Development Moving on to the next AI application in healthcare drugs is discovery and development.…

In the fast-paced world of B2B lead generation, the right tools can make all the difference. Recently, AMELA had the opportunity to explore and integrate Apollo into our business strategies. The experience has been nothing short of transformative, and in this blog, we’re excited to share our journey with Apollo. What is Apollo? Apollo is a comprehensive B2B lead generation platform that allows you to find, engage, and close deals with your ideal customers. With more than 275 million contact databases, 65+ million companies, and 60+ filters, you can easily find the right customers and connect them with Apollo’s engagement tools and features. As a flexible B2B lead generation solution, Apollo is suited for every type of business, from start-up businesses to large ones. For example, Gong, a revenue intelligence platform has taken advantage of Apollo. In detail, Gong increased their qualified lead volume by 200% using Apollo’s precise targeting and automated email sequences. Apollo’s Features You Should Notice We know that Apollo’s website has pointed out all of its features. Though Apollo has a wide range of significant features, after a long time using Apollo,  in this blog, we just mention some of the most outstanding ones of Apollo. And we hope that this will help you a lot. So, let’s check it out! Apollo’s Unparalleled Access to Data Don’t you know that about 95% of emails from Apollo were sent accurately? What does that mean? High email deliverability rates will maximize your outreach impact and connect with the right customers. With a huge database including people who come from multinationals, and have various job titles, organizations can reach a large amount of potential customers. And this number will continue to rise. Why? According to the U.S. Census Bureau, more than 5 million new businesses are launched in 2023. This marks a 10% increase over 2022. Furthermore, the leads’ quality, which is created based on more than 60 filters, is truly good. Apollo provides various kinds of filters, such as demographics, business activities, market segments, etc. For example, in demographic filters, Apollo allows you to filter leads based on job title, seniority, location, language, and more. It also enables you to search for leads based on business activities, such as: Employees Revenue Buying intent Various other criteria related to the current and future status of the business. As you can see below, we apply 6 filters: employees, kind of industry, and buying. And Apollo shows us almost 150 companies that meet the criteria.  Recently, Apollo just has lead scoring. I bet that you don’t know! Lead scoring is a tool in the filter site, it can create exact scoring models. Apollo provides businesses with the ability to create precise and customizable lead-scoring models, giving them full flexibility in defining criteria, weightings, and variables. This empowers companies to design scoring models that align with their unique business goals, target market, and sales process. With Apollo.io, you can leverage a combination of product and marketing data from your CRM system, along…

Did you know that the global AI market size is projected to reach a staggering USD 1.56 trillion by 2030? As we strive into 2024, AI is still transforming our world, including various industries such as healthcare, finance, retail, etc. According to Forbes, nearly 80% of businesses have already adopted or actively explored AI implementation. So, in this blog, we will explore the top 6 AI trends that will continue to change how we live and work in 2024. Let’s check it out! Generative AI The 1st AI trend is Generative AI, which includes algorithms, such as ChatGPT, and Google Bard, that are capable of generating various types of content, including audio, source code, images, text, video, etc. While Generative AI still struggles to accurately generate words in the images it creates, it does not pose a threat to replacing writers and graphic designers. Nevertheless, Generative AI does have the remarkable capability to significantly promote the overall process. It can generate images and text, rephrase content, and even perform fact-checking and grammar corrections. The acceleration brought about by generative AI is not limited to a specific profession or activity. It holds the potential to automate tasks, enhance productivity, reduce costs, and unlock new growth opportunities. This is precisely why the widespread availability of AI content-creation tools that democratize access to information and skills is considered one of the most disruptive AI trends of this decade. Gartner predicts that about 30% of outbound marketing messages might be synthetically generated by 2025. Augmented Working, BYOAI & Shadow AI Move on to the next AI trend - BYOAI or Bring Your Own AI and Shadow AI. But why? As AI technology becomes more accessible and user-friendly, with tools like ChatGPT and other no-code platforms, individuals are increasingly comfortable using AI in their daily lives. This includes the workplace, where employees see the potential of AI to boost their productivity and creativity. According to Forrester’s report, it found that 60% of workers will utilize their own AI to perform tasks. Moreover, companies across various industries are recognizing the immense value of AI, but there’s a shortage of skilled AI professionals. BYOAI allows employees who are already familiar with and proficient in specific AI tools to utilize those skills directly in their work, bridging the talent gap.  Shadow AI, on the other hand, refers to AI assistants who work alongside employees, automating routine tasks and providing real-time support. As a result, this frees up employee time for more complex and strategic work, leading to significant productivity gains. While both BYOAI and Shadow AI offer substantial benefits, there are also challenges to consider, including: Security and compliance: Businesses need to establish clear policies and procedures to ensure the security and compliance of employee-owned AI tools used in the workplace. Integration and interoperability: Integrating various BYOAI tools with existing company systems can be complex, requiring careful planning and configuration. Data privacy and ownership: The most important challenge, concerns about data privacy and ownership need to be addressed…

Do you really know the way to prompt ChatGPT to write code perfectly? As AI continues to advance, language models such as ChatGPT have become increasingly capable of assisting in various tasks, especially code writing. In detail, prompting ChatGPT to generate code can be a powerful tool for developers, enabling them to automate repetitive tasks and explore new programming possibilities. But not all of us know the way to prompt ChatGPT, some users are still struggling to have the desired results. In this blog, we will provide a comprehensive guide on effectively prompting ChatGPT to write code, maximizing its potential while mitigating challenges and biases. Challenges and Limitations of Code Generation with ChatGPT Lack of context awareness: ChatGPT generates code based on the input provided, but it doesn't have a deep understanding of the broader context or project-specific requirements. Therefore, it may generate code that works but doesn't align with the overall architecture or best practices of the project. Limited knowledge of recent updates: According to our recent research, we found that almost ChatGPT's knowledge is based on information available up until September 2021. As a result, it may not be aware of the latest language updates, libraries, or frameworks released after that date. Hence, it might not provide the most up-to-date or optimized solutions for specific programming tasks. Difficulty with complex logic: While ChatGPT can handle simple programming tasks, it may struggle with more complex logic or intricate algorithms. It might generate code that is syntactically correct but inefficient or suboptimal for specific use cases. Lack of error handling: ChatGPT primarily focuses on generating code but may not provide robust error handling or exception management. It's essential to manually review and enhance the generated code to handle edge cases, error scenarios, and input validation. Code generation with ChatGPT is considered a good tool for writing code, nevertheless, in case we do not understand and know how to write a prompt, it can lead to various challenges and limitations. > Related: 4 Generative AI trends can shape the future in 2023 So now, the question is: “How can we Prompt ChatGPT to Write Code Exactly?”  It can be said that using ChatGPT to write code is straightforward. You must provide a prompt or a description of the code you want to generate. Accordingly, ChatGPT will then analyze the prompt and create a code snippet matching the description. Here's a step-by-step guide on how to use ChatGPT to write code: Step 1: Select a programming language ChatGPT can generate code in multiple programming languages such as Python, Java, JavaScript, and more. You must specify the programming language you want it to use when generating the code.  Step 2: Provide ChatGPT with a Prompt The ChatGPT prompt should describe the code you wish to generate. It should be written in natural language and clearly state the desired functionality of the code snippet. For instance, if you want to generate a code snippet that sorts an array of integers, your prompt could be "Create…

The increasingly outstanding role of Generative AI (Artificial Intelligence) in our daily lives is impossible to ignore. It revolutionized various industries and transformed the way we interact with technology. Nowadays, a wide range of AI tools such as ChatGPT and Google Bard will increase your productivity. In addition, some of them become the most crucial assistants of marketing teams like AI image creators or AI short video creators. In this blog, we will show you 5 awesome and free AI tools to help your team’s productivity. Microsoft Designer: Image Creators Microsoft Designer is equipped with an array of features and tools that facilitate the creation of captivating visuals. Whether you're a marketer, content creator, or simply someone who wants to add visual appeal to your work, this software provides a user-friendly interface and an extensive library of resources to bring your ideas to life. One of the standout features of Microsoft Designer: Image Creators is its vast collection of pre-designed templates. These templates serve as a starting point, allowing users to quickly customize and personalize their visuals. With a wide range of categories, users have the flexibility to create visuals for their specific needs. Lumen 5: Video Creators Lumen 5 is an online video creator platform with various tools, that help you to make a video in a few steps. With a vast library of high-quality images, videos, and more, Lumen5 empowers you to enhance your videos with captivating visuals. It also offers a range of customization options, allowing you to personalize your videos with your brand logos, and color schemes. Beyond its user-friendly interface and extensive resource library, Lumen5 embraces the principles of storytelling and visual impact. The platform offers a range of video editing tools that enable you to fine-tune your videos, adding transitions, captions, and effects to enhance their overall quality and engagement. This emphasis on storytelling and visual aesthetics ensures that your videos not only convey information but also evoke emotions and leave a lasting impression on your viewers. JADBio: Auto Machine Learning JADBio is an intuitive machine learning platform designed to be accessible without coding expertise, while still providing powerful knowledge extraction tools. JADBio allows users to upload and analyze curated data from various domains. This versatility makes it particularly valuable for students looking to explore machine learning, such as determining which potato variety will yield the best fry (binary classification). Notably, JADBio offers a lifetime free account, and its user interface is designed to be straightforward and user-friendly. >> Related: Sales Performance Increases 200% With Generative AI Copy.ai: CopyWriter Copy.ai is an exceptional AI tool for digital marketing, offering valuable assistance in enhancing marketing strategies. For those seeking a free AI copywriter, Copy.ai stands out as an excellent choice. With Copy.ai's free AI copywriting tool, generating unique and compelling content becomes effortless. Copy.ai provides a brief description of your desired topic. As a result, you can effortlessly obtain content suitable for various platforms such as blogs, and social media. This tool proves particularly beneficial…

  Currently, AI has been mentioned uncountable times as the innovation of contemporary era with the rich material and potential to exploit. As a technology profession, generative AI field is the competitive and fast-paced market with AI trends updated regularly and even unexpectedly sometimes. Furthermore, AI, besides its function as the machine learning tool with tasks like answering question, translation, or creation. It should be perceived beyond this limit with the broader exposure. Thus, generative AI trends matter significantly, which are utilized for the customer experience ecosystem. Its popularity is undeniable by that governments and business spend on AI technology $500 billion in 2023, according to IDC research. But how will it be used, and what impact will it have? Instead of merely understanding, let's see through with the breakdown of generative AI trends. What is Generative AI? Generative AI algorithms utilize pre-existing data to generate completely novel content that has never before physically existed. The forms are videos, images, sounds, or even computer code. Among AI trends, this one is pretty common with the emergence of chatbot, especially chat GPT and capable of creating text and prose close to being indistinguishable from that created by humans. Similarly, we also have Fliki, Super Creator for making video, or Midjourney, Rocket AI for creating images. It's anticable that its usage will be beyond the scale of individuals or small enterprises to the bigger businesses with a wider range of tasks. In 2023, we can see it used increasingly frequently to create synthetic data that can be used by businesses for all manner of purposes. Using synthetic audio and video data can eliminate the need to film and record speech on video. Workers can simply type what they want the audience to see and hear into your generative tools, and the AI will create it accordingly. Accordingly, here is some generative AI trends worth noticing: Multi-Modal Models Trend If you are working with only one source of information, it is easier to train the AI. However, the results may lack context or supporting information, leading to skewed outcomes. In multimodal AI, two or more streams of information can be processed together. Then, it allows the software to have a better understanding of what it is analyzing. This generative ai trend will help the interaction with AI like human with full sense. Most generative AI tools, algorithms, and language models (LLMs) specialize in simulating one form of expression, such as language, visuals, or sounds. However, there is a growing trend towards "multi-modal" generative AI. The upcoming version of OpenAI's ChatGPT is the example. It will have the ability to understand and interpret images, as well as respond to voice commands. Meta has also demonstrated a model that can combine images, text, audio, depth, and motion data. This approach is expected to become more common in the coming year. Additionally, it will soon be normal to have conversations with AI about pictures or videos. This is similar to how we interact with it about…

Sale is basically activities of email, and conversation which are creative and manual. Sale is not only finding customers and talking about the products with hoping they will buy them. Researching customer behavior, and customizing content to be suitable for particular customers takes a lot of time. Besides, salespeople have to do manually some related tasks such as logging contact in CRM, classifying customer groups, creating deals, and lots of other unnamed manual work. That is why sales are well-suited to the capabilities of generative AI models. Selling is interaction and transaction-intensive, producing large volumes of data, including text from email chains, audio of phone conversations, and video of personal interactions. These are exactly the types of unstructured data the models are designed to work with. The creative and organic nature of selling creates immense opportunities for generative AI to interpret, learn, link, and customize. But to realize the true potential, there are hurdles and challenges to overcome. Generative AI must be non-intrusively embedded into sales processes and operations so sales teams can naturally integrate the capabilities into their workflow. Generative AI sometimes draws wrong, biased, or inconsistent conclusions. Although the publicly accessible models are valuable (hundreds of millions of users like us have already used ChatGPT to query the knowledge base on practically every topic), the true power for sales teams comes when models are customized and fine-tuned on company-specific data and contexts. This can be expensive and requires scarce expertise, including people with significant knowledge of AI and sales. So how can sales organizations harvest the value without wasting energy on heading down unproductive pathways? Before we get into how, consider What AI will assist sales optimizing performance. Remove administrative duties The fact, the more customer you have the more administrative tasks you have to do. If the amount of customers is around 10-100 people, you find it easy to remember every piece of information like the email address, hobbies, behavior, and content of your conversation with them. If there are hundreds of customers you have to care about, it’s impossible to handle the giant information in a manual way. AI can automatically log customers’ email, company, and associated conversations, write emails, respond to proposal requests, and organize notes. Supporting Customers is piece of cake Communicating with customers is much easier than before due to the auto chatbot. But for B2B businesses that mostly communicate with customers through email, the application of AI to email is very limited. Because most current email tools only get customers’ general information. By layering on generative AI, the models can produce better recommendations. One example would be considering customer sentiments gleaned from the nuances of language and subtle signals of customer interest or distrust — in emails, conversations with salespeople, posts on social media sites, and more. Further, the salesperson can collaborate with the system to improve recommendations in real-time. For example, after receiving a suggestion to approach a customer with a new offering, the salesperson can dig deeper — both vertically into the customer’s…

The global economic outlook for 2023 is among the weakest in decades, with global real GDP growth forecast to increase by 2.3% in 2023, further down from 3.3% recorded in 2022. Though global inflation is expected to moderate from 9.1% in 2022 to 6.8% in 2023, it is still at historic highs. The high costs of living, rising interest rates, and ongoing geopolitical uncertainties will continue to dent private consumption and investment in many parts of the world, undermining the global growth outlook. Customers will hesitate to spend money on expensive things due to rising inflation.  The problem for businesses is How to create an environment that encourages customers to buy? The answer is to build a Customer Experience Ecosystem. Create a Customer Experience Ecosystem as the solution. Developing a Customer Experience Ecosystem will be easier than ever thanks to the advancement of generative AI. But what exactly is a customer experience ecosystem, and how can you create one? Let’s find out through this article. What is a customer experience ecosystem? Ecosystem = living and non-living things that make up an environment and affect each other. Customer Experience Ecosystem aka Business Ecosystem includes customers, staff members, distributors, partners, agencies, competitors, rituals (planning, funding, evaluating, rewarding, reporting, communicating, advancing, and training), and the logistics and interactions between all of these stakeholders and rituals. Like a rainforest ecosystem, you must think holistically about the interdependencies of all elements. Think about the food chain, what informs what, who influences whom, who needs whom, what makes things tick, and what gets in the way of success. Therefore, creating an ecosystem for the consumer experience requires an awareness of how ecosystem components interact. Many firms have used customer interactions to collect data, evaluate that data, and then modify their marketing initiatives and business plans to cater to different client segments. They have a better understanding of clients and a better strategy for dealing with them, which makes them stand out from rivals in every way. How can we build a customer experience ecosystem? ・ Building an Intelligent Experience Engine New digital media create new ways for users to interact with brands. Location-based tracking and payment systems activated by the swipe of a hand blur the lines across prepurchase (advertising/marketing), purchase (sales/transaction), and postpurchase (service/loyalty) interactions. These capabilities have created intelligent ways to reshape customer experiences, and they enable brands to be distinctively valuable and deepen engagement. Starbucks, for example, geo-targets lapsed customers who are near its stores with ads about new seasonal beverages, and it sends customers personalized in-app offers to encourage them to visit a store or to try their convenient mobile order-and-pay option. Building an Intelligent Experience Engine means building an end-to-end  experience but focusing on each micro goal on the journey. Think about how to design the flow of a given moment. Because each positive individual moment creates an overall customer experience. At each moment what information should be provided to the customer? Suggestions for customers to use the cross-channel or cross-party which will be most convenient?…