iPads have become so well-known that many people refer to tablets as iPads. They have made a significant impact in the manufacturing business, outperforming rival tablet lines in terms of overall design and machine details. ChatGPT now is gaining popularity as well. When it comes to AI or AI chat bot, most people think about ChatGPT, but there's also Google Bard, Bing Chat, and Claude. In this article, we will find out What is Google Bard, What is ChatGPT and compare rising star ChatGPT vs Google Bard - Google's favourite. What is Google Bard (Germini)? Demis Hassabis, CEO of Google DeepMind, on behalf of the Gemini team introduced Gemini 1.5 Almost a year after its initial launch, Google Bard faced its share of challenges as an AI-powered chatbot. However, it has since made considerable progress through two significant updates to its large language models (LLMs) and multiple enhancements. Google has decided to move beyond the Bard brand, opting for a fresh start with a new name, Gemini. In February 2024, Google announced that the chatbot previously known as Bard will be renamed Gemini, after the LLM that drives it. This change aims to highlight the sophisticated technology that underpins the chatbot, as stated by Google. What is ChatGPT? Crafted through a collaboration between OpenAI and Microsoft, ChatGPT is a conversational AI chatbot capable of responding to queries and executing tasks with human-like interactions. Introduced towards the end of 2022, ChatGPT quickly captivated a global audience with its exceptional capability to produce text that closely resembles human writing. This includes everything from coding snippets, brief document overviews, and song lyrics to comprehensive essays, travel itineraries, and humorous content. The technology's core, an advanced language learning model (LLM), utilizes GPT-3.5 for ChatGPT's free version and GPT-4 for its premium, subscription-based offering. ChatGPT vs Google Bard: General Similar and Differences In simple terms, ChatGPT and Google Bard (Gemini) have a lot in common. Both are AI tools designed for a wide range of tasks and they're aiming for the same users. They're built on a similar foundation known as Large Language Models (LLMs). ChatGPT's latest version runs on OpenAI's GPT-4, while Gemini is driven by Google's PaLM 2 model. If you're curious about LLMs, which are crucial to the current wave of AI advancements, we suggest exploring our course on Large Language Models (LLMs) Concepts. Yet, when you look closely at Gemini and ChatGPT, there are quite a few differences. We've put together a brief overview of the key distinctions in the table that follows. Feature Gemini ChatGPT Underlying LLM PaLM 2 GPT-3.5/GPT-4 Data access Real-time Limited in free version Multimodality Text, image, voice Text only (free version) Integration Google tools Third-party tools Response modes Multiple Single UX Allows users to choose from multiple response modes Only one response mode Pricing Free & $20/month (advanced) Free & $20/month (premium) ChatGPT vs Google Bard (Gemini): Idea Generation Prompt: Please give me 5 ideas for Outbound Marketing Email titles that attract customers to click on…

In the rapidly evolving landscape of digital technology, free generative AI tools have emerged as a game-changer for professionals across various industries, promising not just innovation but also substantial time and cost savings. With the advent of these tools, tasks that once took hours can now be completed in a fraction of the time, harnessing the power of AI to generate content, design, and solutions tailored to specific needs.  A striking example of this efficiency is a study revealing that free generative AI tools can reduce the time spent on certain tasks by up to 40%, opening the transformative potential of these technologies. In this blog, we will delve into the top 10 free generative AI tools, exploring how these tools are incredibly powerful in streamlining workflows and enhancing creativity. Whether you're a developer, designer, or writer, the following list of free generative AI tools promises to be a valuable asset in your toolkit. By the way, it can unlock new possibilities and enable you to achieve more with less. Now, let’s get started! What Exactly is Free Generative AI Tools? Free Generative AI tools refer to AI systems that are available at no cost and are capable of generating new content, or solutions based on the inputs. Unlike traditional AI systems, generative AI goes a step further by creating original outputs. These tools leverage advanced algorithms and machine learning techniques to understand the context and learn from vast datasets. Then, free generative AI tools produce outputs that can range from text, images, and music to code, designs, and more. The "free" aspect of these tools means that they are accessible without financial investment, making advanced AI capabilities available to a broader audience who looking to explore AI's potential without the barrier of cost. This democratization of technology fosters innovation and creativity! It allows users to experiment with AI-driven solutions and integrate them into various projects and workflows. Free generative AI tools can be particularly beneficial for tasks such as content creation, and data analysis, offering a glimpse into the future of AI-driven automation and creativity. 10 Free Generative AI Tools That Can Help You Save Hundreds of Time Chat GPT Until now, ChatGPT stands out as one of the leading free generative AI tools in the industry, renowned for its user-friendly interface. By simply typing a query or prompt and hitting enter, the user activates the tool's NLP capabilities, which meticulously analyze the input to craft a coherent written reply. Designed as a versatile AI companion, ChatGPT can engage in interactive dialogues or assist in generating diverse written materials, including articles, emails, and code. Initially launched in November 2022 with training data up to the year 2021, ChatGPT has since evolved. As of September 27, 2023, it integrates with the Bing search engine, enabling users to access more current information through its interface. However, it's crucial to approach ChatGPT's outputs with a degree of skepticism, as it can occasionally produce or "hallucinate" incorrect information. Verifying the accuracy of its…

Within the dynamic realm of artificial intelligence, Generative AI stands as an outstanding innovation, redefining the creative capabilities of machines. This field has achieved extraordinary progress, from producing artwork and music to composing text with a human touch, captivating enthusiasts and specialists alike. This blog will explore the heart of Generative AI, presenting ten must-know Generative AI examples in 2024 that showcase its profound impact and potential. Let’s check it out! Some Undeniable Benefits of Generative AI Below are some undeniable benefits that generative AI brings to today’s digital era, let’s take a look! Benefits of Generative AI Description Content Generation Creates content for websites and social media, saving time Language Translation Accurate translation between languages, enhancing global communication Artistic Creativity Generates art, music, and poetry, expanding machine creativity Data Augmentation Generates synthetic data to improve machine learning models Chatbots and Virtual Assistants Powers smart chatbots and virtual assistants for user support Medical Diagnosis Aids in medical image analysis and informed decision-making Autonomous Vehicles Enhances self-driving car perception and decision-making Personalization Creates personalized recommendations for products and services Scientific Research Models and simulates complex phenomena, accelerating discoveries Natural Language Understanding Analyzes sentiments, chats, and summarizes data for business insights Top 5 Generative AI Examples in 2024 In 2024, generative AI has taken creativity and efficiency to new heights. Now, we’ll give you the top 5 generative AI examples in order to help you have a deeper understanding of generative AI’s powerful application. Image Generation In the dynamic world of generative AI examples, the magic of Image Generation showcases just how clever generative AI models can be. Generative AI tools like DALL-E 2, MidJourney, Jasper, and Stable Diffusion change the game by turning simple text descriptions into stunning images. How Does This Work? Generative Adversarial Networks (GANs): GANs are the heart of image generation. Why? Image GANs as a duo of neural networks - one is the generator and the other is the discriminator, and they’re in a contrast creative showdown. Generator: This part of the network is like an assisting artist, starting with a blank canvas (random noise) until a masterpiece emerges - an image that looks absolutely real.  Discriminator: The discriminator’s role is to judge the art. Trained on a gallery of real images, it’s got an eye for detail and tries to spot the fakes from the real deal. The ultimate goal for the artist is to fool the discriminator with its creations. Adversarial Training: Here’s where the magic happens - in this ongoing battle of wits between the generator and the discriminator. As the generator gets better, the discriminator has to up its game, leading to even more realistic images being created. Generative AI Examples of Image Generation DeepDream by Google: This tool turns your photos into something out of a dream, making everyday images look like they've jumped out from a fantasy world. [caption id="attachment_2680" align="aligncenter" width="1024"] DeepDream's Website[/caption] Website: https://deepdreamgenerator.com/  StyleGAN by NVIDIA: Ever seen those ultra-realistic faces that look like they belong to someone, but…

As we step into the new year, generative AI is transforming how we work, create, and innovate. From writing content to designing visuals and coding, these generative AI tools are making tasks easier and more efficient.  According to Statista’s statistics, generative AI is cutting down the time it takes to create content by 40%. If you're looking to stay ahead in the tech game, in this blog, we’ll give you the top 10 generative AI tools you should master in 2024. Let’s get started! What Exactly is Generative AI? Generative AI refers to a category of AI technologies and algorithms designed to generate new content or data that is similar to but not identical to the training data it has been fed. This can include text, images, music, voice, videos, and other forms of media or digital content.  A well-known example of generative AI is GPT, which generates human-like text based on the input it receives. These systems rely on complex neural network architectures, such as deep learning and machine learning models, to generate content that can be surprisingly creative and nuanced. The key aspect of generative AI is its ability to create content that was not explicitly programmed or inputted into the system. Instead, it learns from examples to produce entirely new creations that maintain the essence or style of the input data, making it a powerful tool for a wide range of applications, from content creation and design to solve complex problems in innovative ways. Generative AI Tools’ Roles in the Digital Era Generative AI tools are really changing the game in so many areas, and it's pretty exciting to see! Imagine having a tool that can help whip up everything from cool graphics to new software features. That's where generative tools AI come in, making things faster, more creative, and super innovative. Content Creation: In the world of content creation, writers, marketers, and all sorts of creative people are teaming up with generative AI tools to make magic happen. They're using these cool generative AI tools to whip up content faster, making their whole process smoother and cutting down the time they spend on creating stuff by a whole 40%!  Art and Design: Artists and designers are having a breakthrough with generative AI tools, using them to make all kinds of cool art, drawings, and designs that really push the envelope on what's creatively possible. There's even a study that showed when they mix generative AI tools into their design work, they come up with 75% more fresh and attention-grabbing ideas than before. It's like having a creativity turbo-boost! Writing Code: For developers, generative AI tools are like a superhero for coding! It's making coding way easier by coming up with little bits of code on its own, spotting about 30% more bugs than usual, and even offering the best fixes for tricky problems. This means coders can get their work done quicker and make their code even better. Healthcare: In the world of medicine, generative AI…

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…

Learning how to use ChatGPT to write code isn’t about letting AI take over your job; it’s about making your workflow smarter, faster, and less repetitive. At AMELA Technology, we’ve used ChatGPT to build real production systems — from small Python scripts to full API modules — and what we’ve learned is simple: the results depend on how you ask. When you structure your prompts right and guide ChatGPT like a junior developer, it delivers surprisingly clean, testable, and even optimized code. In this blog, you’ll find battle-tested example prompts and practical tips to get high-quality code without endless tweaking. Why Use ChatGPT for Coding? Honestly, if you’ve ever wrestled with a stubborn bug at 2 a.m., you’ll get why ChatGPT is a game-changer for developers. It’s like having that one genius teammate who never sleeps and always has a clean code snippet ready. At AMELA Technology, we use ChatGPT daily — to brainstorm ideas, generate boilerplate code, refactor messy functions, or debug stuff that just won’t run. It doesn’t replace real dev work, but it turbo-charges it. You throw in a quick prompt, and boom — you’ve got a working draft in seconds. What makes it truly powerful is how flexible it is. You can ask ChatGPT to: Explain a function you don’t fully understand. Generate boilerplate code for a new feature. Debug a snippet that keeps throwing an error. Optimize your existing code for readability or performance. For us, it’s become less of a “cool AI trick” and more of a go-to coding buddy that keeps projects moving fast when things get messy. [caption id="attachment_2205" align="aligncenter" width="1024"] How to prompt chat gpt for coding[/caption] How to Use ChatGPT to Write Code (Step-by-step Guide) Here’s the workflow we use at AMELA to get useful, shippable code out of ChatGPT without spending hours cleaning it up. 1. Define what you need — clearly and specifically The biggest mistake people make is asking vague things like “write a Python script” or “build a login system.” ChatGPT isn’t a mind reader — it performs best when you give a tight scope and clear parameters. Before you hit enter, make sure your request includes these 5 basics: Task – What exactly should it do? (e.g., “create an API endpoint that uploads an image to AWS S3”). Tech stack – Specify language, framework, and versions (e.g., Node.js + Express, Python 3.11). Inputs/outputs – Define what data it should handle and return. Constraints – Mention performance, security, or dependency rules (e.g., “avoid external packages”). Output format – Tell it what you want: a function, a class, or a complete file. Pro tip: If your task takes more than three lines to describe, it’s too big. Break it into smaller chunks. ChatGPT works best in short sprints. 2. Ask for a plan first — then the code When working with complex logic or multiple files, start by asking ChatGPT to outline its approach before writing code. For example: “Before coding, give me a brief plan with…

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? Connect…