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    "result": {"data":{"allArticles":{"edges":[{"node":{"excerpt":"","fields":{"slug":"/blog/what-should-every-decision-maker-know-about-the-generative-ai-revolution/"},"frontmatter":{"title":"What should every decision maker know about the Generative AI revolution?","order":null,"content":[{"body":"**Disclaimer**: to make things a bit easier, when I’m referring to AI I mean Generative AI and tools based on Large Language Models (LLMs), like ChatGPT. There’s plenty of different models and tools nowadays, but these are the most recognizable, so I used them as a benchmark for the purpose of this article. \n\n## Which industries can get the most value from Generative AI tools? \n\nI will start with a quite obvious statement, but **AI has become more than just a trend.** Some readers already know that. Generative AI is changing the way we work and create across many sectors, not just in product development. However, a company's ability to leverage these technologies effectively depends on their readiness to adapt to market changes swiftly. The more agile and flexible it is, the better chances it has to get advantage from the change. \n\nFrom my observations, the game development industry is a best example of where these AI tools can have a profound impact. Automation has taken the lead here, simplifying processes and creating content, scenarios, dialogues, voice-overs, and even AI-generated audiobooks. The notion of having AI-created content read out by artificial voices truly pushes the boundary between the digital and the real. At this very moment we can create entire stories and dialogues between game’s characters using only digital sources. They’re indistinguishable from the actors' voices. **This means that a game that you, or your kids, will play next year, will most likely have AI generated voices and scripts**. While this is still supervised by humans, the change has already been made.\n\nThis is just the first example I can think of. Potential implementations of Generative AI are vast and span across various industries and the possibilities are almost endless. As you can see from the example, every industry where AI can imitate human interaction can take advantage of this technology.\n\n**But, it's crucial for leaders to use Generative AI responsibly to get its full benefits and avoid any downsides**. In doing so, this technology can be a game-changer, helping industries become more efficient and forward-looking.\n\n<RelatedArticle title=\"Will ChatGPT replace the Google Search Engine?\"/>\n\n## How can AI support acquiring new skills?\n\nFrom my own experience AI has altered how we learn and acquire new skills, particularly in the programming world. That’s clear for everyone who’s working in the software development industry.\n\nSo honestly, if you've been waiting for the right moment to kickstart your coding journey, there's no better time than now. **Tools like ChatGPT is like the teacher we all dreamed of having** – incredibly patient, full of insights, and it's always there for you, ready to take on even the trickiest of your queries. And the best part? It'll never tire of your questions. Instead, it swiftly comes up with accurate answers, making the learning process much easier and less frustrating.\n\nWhat really excites me about AI's role in teaching programming is that it's not just for us, coding veterans. It’s a helping hand to everyone, even those who haven't written a single line of code before. AI has opened the door for learners to effortlessly tap into fields like machine learning or computer vision. Tools like CoPilot radically simplify the life of a software developer, regardless of their experience level. Making cross-domain skill application so much simpler, but of course - it still demands some technical skills. \n\nFrom my own experience, AI's role in helping us acquire new skills is reshaping how we learn, and it's unlocking potential for personal and professional growth. So if you're contemplating beginning your programming journey, I say, go for it! The AI will be a great companion and guide on this journey.\n\n![Max Salamonowicz](/img/Max_Salamonowicz_at_Bolare_s_hackaton.jpg \"Max Salamonowicz\")\n\n## What skills are necessary to make the most of LLM-based tools?\n\nThe real value of AI technologies can be amplified with skills that are not necessarily connected with programming or technological skills. Being able to think algorithmically and comprehend cause-and-effect relationships is crucial, without a doubt, but that’s not all.\n\nFrom my experience, great communication skills to express ideas with precision becomes equally important. Proficient communication, along with empathetic human abilities, enables users to articulate their thoughts plainly, using suitable language and expressions can improve results of the communication between the user and LLMs like ChatGPT. \n\nIt's important to pay attention to how we ask questions to AI. This helps avoid bias or unfairness in AI's answers. By skillfully avoiding unintended influences, professionals can make sure that the AI's output matches what they aimed for. But even then, it’s worth remembering that LLMs have a tendency to hallucinate, so extra precaution when dealing with some outputs is recommended. \n\n**To sum it up, having a mix of coding knowledge and “soft” skills enables people to use AI tools better.** It also helps us to understand how the tools are working and how to make better use of them. \n\n<AiExpertsContactCtaBanner\n  id=\"aiexpertscontactcta-optimization-banner-click\"\n  bannerType=\"developmentOptimizationBanner\"\n/>\n\n\n## You manage an IT or software related department or company? Here’s how to implement AI efficiently\n\nWhen you're leading a large department and your goal is to incorporate innovations using Generative AI, having a clear strategy is the key. The first step involves reaching out to experts in the AI field (like me!) for advice and fine-tuning your plan. Their insight can guide you, ensuring your strategy is in line with best practices and industry standards.\n\nCreating an innovative and collaborative culture within your department is the next step. **Consider hosting a hackathon, like Boldare did, as this provides a space for your team members to voice any concerns, contribute ideas, and help develop AI solutions.** This not only gives your team more agency but also encourages a sense of shared responsibility.\n\nThe success of AI projects hinges on providing your team with unrestricted access to tools like Chat GPT or CoPilot. This enables them to thoroughly explore and harness the technology, fostering productive work that's facilitated by AI. **A quote by John Cleese, a key member of Monty Python, conveys this concept beautifully: “*If you want creative workers, give them enough time to play.*”** Brilliant, isn’t it?\n\n**In a nutshell:** Implementing Generative AI in your department or company requires a clear strategy that includes expert advice, fostering an innovative and collaborative culture, and, last not least, providing unrestricted access to tools like Chat GPT or others - depending on actual needs. \n\n<RelatedArticle title=\"ChatGPT implementation: key takeaways from our internal projects\"/>\n\n## Which companies, outside of Big Tech, are great inspiration when it comes to use of Generative AI?\n\nGenerative AI is impacting more than just Big Tech and tech-focused companies. Take the government of Iceland, for instance. They built  a dedicated department using ChatGPT 4 to protect their national identity. [They employ a GPT model](https://openai.com/customer-stories/government-of-iceland), specifically trained for preserving their rich cultural heritage, putting an emphasis on their language. Another, really great use of Generative AI, is a project that I’m involved in - it’s a sign language interpreter that will be able to translate sign language in real time. It’s one of my favorite use cases - not only is it amazingly needed, but it goes beyond typical, programming related scenarios. \n\nThose are examples that technology can influence literally any area of life or work. It’s only up to use, how we will use it.\n\n## On the other hand…\n\nMicrosoft's leadership in the implementation of Generative AI stands out as both impressive and somewhat … unexpected. Their progress has not been without its challenges - [the Bing setback](https://time.com/6256529/bing-openai-chatgpt-danger-alignment/) is a notable example - but their success has been noteworthy. The company's approach to deploying this innovative AI-related technology cannot be overstated. In my opinion (and presumably, not only in mine), Microsoft has outpaced firms like Google, who typically keep their advancements closely guarded. Moreover, it's really interesting how Microsoft transformed from a software-focused company to one that now masters a service-oriented model. This change shows their flexibility and bold vision for the future. As Generative AI changes the tech world, Microsoft's leading role is key in guiding this change.\n\n## Generative AI will change the marketing\n\nThe transformative potential of Generative AI in the marketing sector is clear, with SaaS tools ranging from generating content to creating appealing visuals. Its real power, however, lies in the automation of complex marketing tasks, thus driving operational efficiency. An example that comes to mind is a colleague who has used LLM tools for executing well-orchestrated Facebook campaigns, improving their efficiency, and saving his valuable time at the same time. \n\nLooking ahead, it's easy to see companies capitalizing on Generative AI for creating tools to automate marketing campaigns on the scale that we have never seen before. **The technology enables the extraction of valuable customer insights and the fine-tuning of marketing efforts, improving personalization and engagement.** Importantly, AI tools can also streamline the process of analyzing campaign results, freeing up marketers to focus more on creative and strategic pursuits. Still, human understanding is crucial when interpreting and applying AI-generated insights, as it ensures that marketing strategies are in tune with audience preferences and brand objectives. Generative AI becomes a key part of marketing, helping brands to bond with their customers better and faster, improving ROI. \n\n## How will AI affect human labor?\n\nThe ongoing AI revolution and its growing influence across various sectors sparks important and unavoidable discussions about its effects on human labor. In my opinion, the rise of AI-driven content creation doesn't lessen the value of human effort. Instead it amplifies our creativity and saves time that can be spent on other aspects of work. We all love to watch beautiful graphics created using software like Midjourney or Stable Diffusion (two of my personal favorites!). Tools like ChatGPT are handy for content creation, but there remains a significant demand for content created by humans, even if it's AI-assisted. **And let's make it clear - using ChatGPT-based tools for content or graphic design is perfectly fine!** They're designed for that purpose!\n\n**In a similar vein, within product development ecosystems like the one in which Boldare works, a valuable product that caters to users' needs can't solely be the work of AI-powered tools.** Sure, tools like CoPilot are incredibly useful, but they can't substitute the hard-earned experience of developers, product designers, and other experts gained over years of building digital products. The human element and experience remain integral to creation - solutions based on Large Language Models (LLMs) are tools, not replacements for human talent.\n\nIn the end, as AI improves, it's clear that the future of work will involve AI helping us, not competing with us. This balance of AI and human creativity can boost industries, start new trends, and highlight the continued importance of human skill in our increasingly digital world. But won’t replace the experience and human empathy towards customers.\n\n![Boldare's hackathon](/img/Boldare_s_hackathon.jpg \"Boldare's hackathon\")\n\n## What should we expect from AI in the near future?\n\n**Looking to the future of LLMs, I expect a shift towards more focused, efficient and lighter models.** They'll be fine-tuned for different needs and sectors. Most probably, companies will have their own AI models that match their goals and frameworks. In short, we'll have AI models for every possible purpose. \n\nMoving forward, we need to be aware of possible hurdles linked to AI growth. A major concern is the tendency to overlook AI's importance or view it as a passing fad, which could limit innovation and progress in different sectors. Plus, the rise in AI-produced content could lead to a flood of misleading data, creating information overload and causing public confusion.\n\nDependence on Large Language Models (LLMs) can result in unwise choices if these systems are mistaken for being superior to complex, expert mechanisms. Can’t stress this enough: we must understand that AI is designed to be a powerful tool that supplements human abilities, not an alternative to human judgment and critical thought.\n\n<EngagementBannerAI\n  title=\"Want to see your app integrated with AI?\"\n  buttonText=\"Set up a call\"\n  description=\"Set up a call, and we will create a working proof of concept for you, even on the same day\"\n  withArrows=\"{true}\"\n/>\n\n## Conclusion\n\nThe well-known **Netflix series \"Black Mirror\"** effectively showcases (as seen in the episode \"Be Right Back\" or others) the need for careful deployment of potent technologies like AI, as rushed application could result in unexpected and possibly damaging outcomes. Therefore, it is vital to be cautious and responsible when adopting Generative AI, so as to leverage its advantages while steering clear of potential pitfalls.\n\nWhile it's important not to be too concerned by negative possibilities, I'm hopeful about the power of **Large Language Models**. I believe the near future is full of promise for AI, with smaller, tailored models pushing various industries forward. But, we need to be careful and alert as we face possible challenges. By using AI wisely and understanding its limits, we're well-prepared to overcome these issues, using this transformative technology to improve society and our shared future.\n\n**About the author: Max Salamonowicz is a robotics engineer known for his innovative work with BeSteady Ltd and ACR Systems.** He has designed hardware used on numerous professional movie sets and is a co-author of the hybrid board game 'Beyond Humanity: Colonies'. Recognized as one of 2015's '50 Most Creative In Business' by BRIEF Magazine, Max is also a crowdfunding expert, having consulted on over 30 campaigns, most of which achieved their desired backing. Though he describes himself as a 'lazy AF ex-coder', Max is an AI/ML expert, project manager, game developer, drone enthusiast, and robotics devotee, showcasing his multifaceted talent in technology, crowdfunding, and game development.\n\n**Disclaimer:** The primary graphic design in this article was created with the assistance of the **Midjourney** app.\n\n![Max Salamonowicz at Boldare's Devcamp](/img/Max_Salamonowicz_at_Boldare_s_Devcamp.jpg \"Max Salamonowicz at Boldare's Devcamp\")"}],"job":null,"photo":null,"slug":null,"cover":"/img/What_should_every_decision_maker_know_about_the_Generative_AI_revolution.png","lead":"**Generative AI isn't just a fleeting tech trend.** It's a powerful force changing many sectors and it is already happening. It's crucial for decision makers to grasp the idea, together with its chances and threats. I wrote this article to help you explore how Generative AI is reinventing not only product development and IT services, but also impacting a variety of other fields. **By sharing my experiences, I hope to highlight the game-changing potential of Generative AI to aid better decision-making**. I encourage all leaders and strategists to read this, and I hope you find it useful!","templateKey":"article-page","specialArticle":false,"isNewWork":null,"isNewNormal":null,"service":null,"settings":{"date":"2023-09-06T09:23:08.265Z","slug":"what-decision-makers-need-to-know-generative-ai-revolution","type":"blog","slugType":null,"category":null,"additionalCategories":["Future","Digital Product","Tech"],"url":null},"author":"Max Salamonowicz","authorAdditional":"","box":{"content":{"title":"What should every decision maker know about the Generative AI revolution?","tileDescription":"Generative AI isn't just a fleeting tech trend. It's a powerful force changing many sectors and it is already happening. It's crucial for decision makers to grasp the idea, together with its chances and threats. I wrote this article to help you explore how Generative AI is reinventing not only product development and IT services, but also impacting a variety of other fields. By sharing my experiences, I hope to highlight the game-changing potential of Generative AI to aid better decision-making. I encourage all leaders and strategists to read this, and I hope you find it useful!\n","coverImage":"/img/What_should_every_decision_maker_know_about_the_Generative_AI_revolution.png","tags":null},"coverImage":null,"settings":null,"type":"BLOG"}},"id":"090d4d05-ca69-5a80-bd95-ca1cc97a8a2c"}},{"node":{"excerpt":"","fields":{"slug":"/blog/will-chatgpt-replace-the-google-search-engine/"},"frontmatter":{"title":"Will ChatGPT replace the Google Search Engine?","order":null,"content":[{"body":"## What is ChatGPT if it’s not a search engine?\n\nChatGPT has taken the digital sector by storm, conquering hearts and minds alike. And this has happened for a reason. It’s easy to use, free of charge, and full of potential uses. It’s powerful, but not unlimited. In fact, I often see how its powers are overestimated and put to use in ways it’s not able to perform. \n\nOne such undoable task is searching for information. \n\nThis may not matter to users who mostly look at the UI and the end result only. **At this level, Google Search and ChatGPT do look similar.** There’s a field where you enter your query, and then you receive some output: for Google, this is a list of websites (not only, though: in recent years, Google has started showing so-called rich results, which are meant to answer the user’s question at the search engine level); for ChatGPT, this is a full answer to a given question. \n\n<RelatedArticle title=\"Kickstart your first AI-based product quicker with our open-source library!\"/>\n\n### AI algorithms in Google Search\n\n**For the sake of clarity, let me emphasize this: Google vs ChatGPT is not simply about a competition between a classic search engine and AI.** Google has used AI algorithms to respond to user queries for some time now ([source](https://searchengineland.com/how-google-uses-artificial-intelligence-in-google-search-379746))[.](https://searchengineland.com/how-google-uses-artificial-intelligence-in-google-search-379746) **RankBrain, Neural Matching, Bert, MUM – these are the most popular AI algorithms that Google has introduced to its search engine in the past years.** \n\nBERT (Bidirectional Encoder Representations from Transformers) was launched in 2018 and it supports the search engine in processing and understanding natural language. It’s based on the Transformer architecture – just like the GPT model used by ChatGPT. \n\n## How does ChatGPT work?\n\n**ChatGPT is a probabilistic language model designed to follow and implement instructions.** It has been trained on a specific set of textual data to perform the instructions as accurately as possible. It does so by generating tokens: sequences of characters and words, based on probability distribution.\n\nTo put it simply, what artificial intelligence basically does is analyze the statistics and sequentiality of word order and build strings of the most probable words ([source](https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/)). The aspect that is not yet visible in ChatGPT itself – but will be visible in its Bing iteration or the OpenAI Playground source model – is the possibility of defining the “temperature” parameter. This feature allows users to decide how much the model can deviate from the information it has learned from its dataset ([source](https://arstechnica.com/information-technology/2023/03/microsoft-equips-bing-chat-with-multiple-personalities-creative-balanced-precise/)).\n\nIn practice, **the temperature parameter tells you whether the tokens (words) used should have the highest probability level**. This has an enormous impact on the final effect. If you decide to add only the most probable words, the output will be very flat, repetitive, and schematic. Once you allow the use of lower-ranking, more random tokens, you will get a more versatile and interesting output. \n\n<RelatedArticle title=\"How to Boost Your Website Traffic with AI: Insights from an SEO Expert\"/>\n\n### ChatGPT is not lying – it’s hallucinating\n\nObviously, **AI’s responses get corrected in the process of fine-tuning, where the generated output is evaluated both by a human and by another, feedback-oriented model**. As a result, the text generated by ChatGPT is more than a purely random patchwork of words – although sometimes it is just that. This randomness means that ChatGPT tends to [hallucinate](https://bernardmarr.com/chatgpt-what-are-hallucinations-and-why-are-they-a-problem-for-ai-systems/). \n\n> In other words, ChatGPT may generate an output which sounds plausible but has nothing to do with the facts. \n\nFor example, when asked about some scientific subject, it may cite particular research papers, along with their titles, authors, publication dates, etc.But once you start searching for these papers, it often turns out they have never existed. It all depends on how much information and how many citations on a given subject there were in the text corpus used for training the model. \n\n**Hallucinations happen because, even though the models are trained on huge amounts of textual data, they are not able to understand the world in a human way**, or to verify the truthfulness of information like people would do. Instead, they rely on language structures and patterns learned from the training data.\n\n**Consequently, even if the output generated by a model is grammatically correct and sounds sensible, it may contain false information – or information “invented” by the model.** This is where the concept of “hallucination” comes from.\n\nAnd this is why you must bear in mind that although AI may be a powerful tool for text generation, it still requires human supervision and evaluation, especially if the information it provides is meant to be used for making important decisions or in situations where the use of precise and accurate data is essential. **This is why using ChatGPT as an alternative to search engines – including Google – is practically out of the question.** \n\n### Will ChatGPT replace search engines?\n\n**ChatGPT is not a search engine – it’s a text processor.** As the name suggests, its function is to process text. It can generate texts as well, but to do that, it must receive some input or a pattern to follow. It won’t write a blog post for you (I mean, it can, but the writer must still fact-check the information generated by the chatbot). \n\n### What can we use ChatGPT for?\n\nI use it myself: I do this in a specific and well-tested workflow, though. I start by providing a list of details that I want to be included in the text. This allows me to limit the potential hallucinations. When I collect this information, I fact-check it and do preliminary research – I can’t imagine replacing Google with ChatGPT in this respect. ChatGPT may come in handy for various uses: it can code, proofread, analyze and categorize content, and so on. But it won’t work as a search engine. \n\n<RelatedArticle title=\"ChatGPT's risks and pitfalls: what you need to know before implementing it in your product\"/>\n\n## Will ChatGPT replace Google search? Google I/O 2023\n\nAs far as the competition between ChatGPT and Google is concerned, I need to draw your attention to the recent announcements from the [Google I/O 2023](https://blog.google/technology/ai/google-io-2023-keynote-sundar-pichai/) event. It turns out that the world’s most popular search engine is also going to present search results generated by artificial intelligence. And this is not about Bard, Google’s answer to ChatGPT, which, by the way, [got a massive upgrade](https://mashable.com/article/google-bard-search-announcement-io-2023) at the conference. It now works much better than the OpenAI product, because it’s able to analyze the content of particular URLs – and ChatGPT isn’t capable of doing that yet. [OpenAI has already announced](https://help.openai.com/en/articles/6825453-chatgpt-release-notes) that a beta version of this feature will be released by mid-May for the paid plan subscribers. **So far, ChatGPT can only hallucinate about website content, based on – most probably – the phrases in the URL.** Bard can also respond to queries about current events, whereas ChatGPT makes it clear that its knowledge is limited up to 2021. \n\n[As we can learn from the announcements](https://blog.google/products/search/generative-ai-search/), the results generated by AI in Google Search will respond to long-tail queries. This means queries which are so specific that there are no relevant organic search results. It is not likely that AI-generated search results will respond to all, or even most queries. [Generating such results costs 10 times more than a standard keyword search](https://arstechnica.com/gadgets/2023/02/chatgpt-style-search-represents-a-10x-cost-increase-for-google-microsoft/), even with additional elements.\n\n![Will ChatGPT replace the Google Search Engine?](/img/Google_Search.png \"Will ChatGPT replace the Google Search Engine?\")\n\nThe new, rather conspicuous box with the AI output, will affect CTRs, also for text ads. So, if Google covers too many keywords with AI boxes, in particular the keywords that are lucrative for advertisers, and, as a result, it blocks SERP-generated website traffic, advertisers will leave Google. It seems unlikely that Google will decide to kill off its main source of income. \n\n<RelatedArticle title=\"The Agile Product Builders Community: a network for professionals\"/>\n\n### What does this mean for businesses that rely heavily on SEO?\n\nWhat does this all mean for businesses whose main source of income and lead generation is organic reach? **Chatbots like ChatGPT and AI boxes visible in Google both work better in the case of strictly informational queries: questions which only have one correct answer**. The users that are to be converted will have to look for their answers on the websites anyway, because it’s impossible to convert directly from the search engine result page. At least for now.\n\nThe difference may be visible in the [user journey](https://www.boldare.com/blog/define-user-journeys-to-increase-user-engagement/). AI boxes may take over the traffic from the content that was supposed to educate customers. Now, the question is – will it be possible to measure (for example, from the level of Google Search Console) how often given content is used by Google AI to generate the new type of results? \n\nLet me give you an example, or a fun fact. When asked about the best SEO agencies in Poland, both ChatGPT and Google’s Bard give Delante as their top answer.\n\n![Will ChatGPT replace the Google Search Engine?](/img/ChatGPT_question.png \"Will ChatGPT replace the Google Search Engine?\")\n\n![Will ChatGPT replace the Google Search Engine?](/img/Examplatory_question_to_ChatGPT.png \"Will ChatGPT replace the Google Search Engine?\")\n\nWe’ve checked that multiple times in the last couple of months, using various devices and accounts which are not connected with the company. One or two clients, when asked how they’d found out about us, told us that they’d learned about us from ChatGPT. \n\n**A new term has already been coined by the SEO industry: AIO, that is – Artificial Intelligence Optimization.** Our success in this area was a huge surprise to me (despite our strong engagement in SEO). My theory is that the key factors were off-site in this case. As many trusted domains mention us and link to us (e.g. our high-ranking Clutch profile) AI models consider us recommendable. This means that the key to AIO will be off-site SEO.\n\n### Is content still king?\n\nSo, what about website content creation, which has reigned over digital marketing in the past years? **AI tools like ChatGPT can be used to create content in a cheaper and quicker way.** However, this leads to content inflation. You will no longer build a competitive advantage just by having an extensive blog with thousands of substantial and specialized articles. \n\nIt seems that we are in a transition period where mass and automated website content generation still makes it possible to achieve better results. The more websites start doing this, though, the weaker outcomes the strategy will bring. The way users consume content is changing towards shorter and more condensed forms, both in terms of text and video (just take a look at TikTok or YouTube Reels) – and AI will only contribute to this trend. \n\nIt’s worth remembering here that AI models are able to create not only texts but also graphics, photos, music, and videos. Of course, texts are the easiest and cheapest to create but we should expect the entry threshold for creating multimedia content to also become lower. \n\nSo, **although AI allows creating content in a cheap way, the key factor is going to be the unique, original, and factual qualities of this content**. To ensure these qualities, you will need a human with unconventional ideas and a creative attitude. Artificial intelligence will be used to find inspiration and coordinate the creative process, so it will get relatively cheaper. At the same time, the expert will play a crucial role in the process by bringing true value to generative AI.\n\n### More AI tools\n\nAI makes it possible to produce not only more and more content but also code and software scripts – that is, tools. Numerous startups have begun to spring up, claiming to offer better versions of ChatGPT, while in fact, they mostly want to go with the AI hype flow. \n\nTwo aspects are worth highlighting in this trend. **Many tools, especially those created in Q4 2022 and Q1 2023, are based on the OpenAI API.** So, they are based on the GPT model. However, to optimize costs, they are usually based on the older (and cheaper) models, which generate outputs of much lower quality. What follows is that instead of looking for go-betweens (like JasperAI), it’s a better idea to integrate the model independently through the API. After all, ChatGPT itself can help you write the necessary code. \n\nOn the other hand, [as the recently leaked Google document suggests](https://www.semianalysis.com/p/google-we-have-no-moat-and-neither), the company fears that it will lose the AI technology race, not to OpenAI, but to smaller contestants. Open-source models trained on smaller but precisely curated datasets are cheaper and take less time to train. This way, they offer better flexibility. \n\n“They are doing things with $100 and 13B params that we struggle with at $10M and 540B,” the note reads. It may be concluded that, instead of relying on ready-made solutions, you can start learning how to train your own AI models, for your own needs. According to the document leaked from Google, you only need one evening to do that. \n\n<RelatedArticle title=\"Ethical Issues with AI for Digital Product Development\"/>\n\n## Will ChatGPT replace the Google Search Engine? – Summary\n\n**Let’s sum it up – it’s very unlikely that ChatGPT will replace Google Search.** From a technological perspective, they are two different tools. **ChatGPT is not a search engine and it shouldn’t be treated as one.** What’s more, Google – despite a momentary slowdown in Q1 2023 in terms of AI and language models – is not going to lose ground to OpenAI. \n\nThis discipline is growing so dynamically at the moment that it’s really hard to make any sensible predictions. What we know for sure is that there are two big players and a number of smaller entities working on AI who are able to react better and quicker to technological and business changes than the tech giants. For end users, this competitive environment may mean that there will be more and more high-quality and relatively accessible tools based on artificial intelligence. The only question that remains is – are we going to leverage their potential in the right way?\n\n**About the author:** Wojciech is a SEO R&D Specialist at [Delante](https://delante.co/), the SEO agency we work with. He has over five years of SEO experience with specializations in web analytics, technical SEO, legal industries, and news portal positioning. His expertise includes optimizing websites, analyzing data, and addressing the specific needs of legal industries. Wojciech excels in strategically positioning news portals to maximize visibility and engagement.\n\n**Disclaimer:** The primary graphic design in this article was created with the assistance of the Midjourney app.\n\n<AiAssistantBanner fullWidth={true} />"}],"job":null,"photo":null,"slug":null,"cover":"/img/Will_ChatGPT_replace_Google_search_engine_1.png","lead":"Long story short: no, **ChatGPT will not replace the Google Search Engine**. It might take over some traffic but, at least for now, it’s unable to turn the search engine market upside down. And that’s because it’s hallucinating.","templateKey":"article-page","specialArticle":false,"isNewWork":null,"isNewNormal":null,"service":null,"settings":{"date":"2023-05-26T08:40:40.574Z","slug":"will-chatgpt-replace-google-search-engine","type":"blog","slugType":null,"category":null,"additionalCategories":["Digital Product"],"url":null},"author":"Wojciech Urban","authorAdditional":"","box":{"content":{"title":"Will ChatGPT replace the Google Search Engine?","tileDescription":"No, ChatGPT will not replace the Google Search Engine. It might take over some traffic but, at least for now, it’s unable to turn the search engine market upside down. And that’s because it’s hallucinating.","coverImage":"/img/Will_ChatGPT_replace_Google_search_engine_1.png","tags":null},"coverImage":null,"settings":null,"type":"BLOG"}},"id":"bdedc46b-e80d-590c-96fd-697244868f4e"}},{"node":{"excerpt":"","fields":{"slug":"/blog/chatgpt-implementation-key-takeaways-from-our-internal-projects/"},"frontmatter":{"title":"ChatGPT implementation: key takeaways from our internal projects","order":null,"content":[{"body":"**Disclaimer:** ‘ChatGPT’ is an app that is based on the **‘GPT’ model** created by OpenAI. However, for the purposes of this article we use both terms interchangeably. While working with this model we used mostly the **GPT 3.5** and **3.5 Turbo** versions.\n\n## It’s a revolution!\n\n**ChatGPT** (and other GPT models) will revolutionize the [software development](www.boldare.com) market. However, the exact nature of the revolution remains unclear. The possibilities are endless, limited only by our creativity and the technical boundaries of the model. However, with each release and new version of **GPT**, these limitations become less problematic with newer, more efficient models, allowing us to handle more data and provide more user-friendly, out-of-the-box solutions that are easy to implement.\n\n## Build and learn\n\nOne of the best ways to learn about GPT's capabilities is to adopt a [proof of concept (POC) approach](https://www.boldare.com/blog/what-is-proof-concept/). In product development, a **POC** provides practical evidence of the technical feasibility (or not) of an idea. Using this approach, we were able to test multiple ideas and verify our assumptions with data inputs and prompts, helping us to quickly validate hypotheses and gather valuable information for future implementations before any code is even written.\n\nWe need to put emphasis also on the process of prompting - understanding how to build and fine-tune prompts is an essential part of working with ChatGPT or similar AI apps. Iterative and intensive testing of results is crucial here. \n\nTherefore, we suggest brainstorming, playing with **ChatGPT**, creating POCs and prototypes, making mistakes, and learning from them. In the near future, as GPT models improve in efficiency, security, and reliability, previous experience with the technology will be extremely valuable to businesses seeking to benefit from it quickly.\n\n<RelatedArticle title=\"Lean Startup Series: Traveling the Build-Measure-Learn Cycle\"/>\n\n## Text only\n\nDespite promising visions of the future, it's important to note that GPT is currently a language model limited to processing and outputting plain text through the publicly available **OpenAI API**. GPT version 3.5 may not be suitable for nuanced tasks that rely on multiple variables and up-to-date data, as the model is limited to the data available from 2021. Therefore, if we want to create something reliable, it is important to feed the model with up-to-date information, leaving the model to format the final user-readable output, rather than relying on GPT’s general knowledge about the world.\n\n## Low reliability... for now\n\nWhen we consider the number of new AI-powered tools, it's hard to believe that AI and **LLM (large language model)** technology is still in its infancy. However, **ChatGPT has limited capabilities** and may not be the best choice for businesses that want to use API-based AI solutions as a primary product feature. It's impossible to guarantee high performance and uninterrupted access to the API. \n\nAt the moment, the OpenAI service is unstable and inefficient, and solutions based on it still have a lot of room for improvement. That being said, we obviously know that it can visibly improve certain workflows and assist in building digital products, without being directly involved in their critical features.\n\n## Data is like oxygen \n\nAlthough it may sound harsh, **GPT without latest data can be useless for many business applications** - much like any other large language model. As ChatGPT’s popularity grows, the value of reliable and truthful data sources will increase exponentially. As a result, many companies that provide access to content (such as media corporations, magazines, and data warehouses) will restrict access to their data behind paywalls. This will make it more difficult to access reliable data for projects that rely on it. Those who have access to such data on their servers will also be able to consider an additional line of business by providing reliable content for a fee.\n\n<RelatedArticle title=\"Kickstart your first AI-based product quicker with our open-source library!\"/>\n\nFrom an engineering perspective, the most significant challenge of any product that uses GPT is **ensuring that the data is properly prepared**. Connecting data with GPT or other models is relatively straightforward for someone with experience in product development. If you plan to create an app that uses a specific dataset, you need to know how to prepare the data correctly and seeking assistance from a professional data engineer may be a good idea.\n\n![Here's an example of how Midjourney, an AI-based tool, interprets the collage style from Boldare's brand book](/img/Midjourney.png \"Here's an example of how Midjourney, an AI-based tool, interprets the collage style from Boldare's brand book\")\n\n<ImageCaption content=\"Here's an example of how Midjourney, an AI-based tool, interprets the collage style from Boldare's brand book.\" />\n\n## Vector databases \n\nOnce we started working on **ChatGPT**-based features, we realized how crucial vector databases are.\n\nYou can think of a vector database as the long-term memory of your AI app. These databases store learned input representations - typically a text document along with an embedding vector (a list of numbers representing the **LLM’s** “notion” of a particular document). These documents can later be queried with AI and used to improve the output of language models.\n\nProperly maintaining and curating vector databases can greatly improve ChatGPT's accuracy and quality. This involves regularly updating the database with new information, removing irrelevant data, and optimizing for the implementation's specific use case. Managing the vector database carefully can improve ChatGPT's performance and effectiveness.\n\n<RelatedArticle title=\"How much does it cost to develop an app?\"/>\n\n## Brace yourselves, regulations are coming \n\nWhile working on our internal **PoCs** here at Boldare, we have learned that even though GPT can do amazing things and offers endless possibilities, we need to be careful about the data we collect and use. This means encrypting data, controlling access, and regularly checking the system for vulnerabilities. We also need to ensure that user data is only used for the intended purposes, and that users are informed about how their data is being used.\n\nBy prioritizing security and privacy from the outset of working with **ChatGPT**, it will be easier to comply with upcoming legislation, such as regulations implemented by organizations like the European Union (e.g. **GDPR**). \n\n## Will it replace people? \n\nOne of the valuable lessons we learned: \n\n> **AI won’t replace experts, but people who know how to make use of AI will.**\n\nTo make effective use of AI, a development team needs to acquaint itself with a variety of new technologies, learn how to load data efficiently within data limits, and be aware of the available databases and mechanisms for a given use case. Since new **AI-related technologies are released every week**, companies must invest significant effort into staying up to date. It's essential to invest in the skills of both developers and non-developers.\n\n<RelatedArticle title=\"Benefits and practical aspects of working without project managers\"/>\n\n## Not just GPT\n\nGPT is only one of many models available at the moment. If you want to explore different tools we recommend **Hugging Face** - a very vivid community and library of models for different purposes like speech to text, text to graphic, audio to audio, video classification, etc. \n\n## Lessons learned - a summary\n\n**We won’t stop here with our GPT and AI-related works.** Our research and development team is still working on various projects, ranging from small but helpful apps like Slack-based virtual assistants to more complex features and tools that we can offer as parts of our partners' products. **There’s plenty to discover and learn, and fortunately, we're pretty good at learning!** If you have any questions, related or not, feel free to let us know.\n\n<AiAssistantBanner fullWidth={true} />"}],"job":null,"photo":null,"slug":null,"cover":"/img/What_have_we_learned_using_ChatGPT_for_internal_projects.png","lead":"At Boldare we have a **‘hands-on’ approach**, and that’s why we decided to explore the **ChatGPT** topic by using it rather than reading about it. Our **research & development team** spent last month brainstorming, drafting, implementing, and coding AI-powered apps. In this article, we'll share nine lessons we've learned about the **GPT model**, including the significance of vector databases, security concerns, and the importance of data. We hope you’ll find them helpful!","templateKey":"article-page","specialArticle":false,"isNewWork":null,"isNewNormal":null,"service":null,"settings":{"date":"2023-05-10T09:43:22.582Z","slug":"chatgpt-implementation-key-takeaways-from-our-projects","type":"blog","slugType":null,"category":null,"additionalCategories":["Digital Product"],"url":null},"author":"Kamil Szydłowski","authorAdditional":"Romuald Członkowski","box":{"content":{"title":"ChatGPT implementation: key takeaways from our internal projects","tileDescription":"At Boldare we have a ‘hands-on’ approach, and that’s why we decided to explore the ChatGPT topic by using it rather than reading about it. Our research & development team spent last month brainstorming, drafting, implementing, and coding AI-powered prototypes. In this article, we’ll share nine lessons we’ve learned about the GPT model, including the significance of vector databases, security concerns, and the importance of data. We hope you’ll find them helpful!","coverImage":"/img/What_have_we_learned_using_ChatGPT_for_internal_projects.png","tags":null},"coverImage":null,"settings":null,"type":"BLOG"}},"id":"34f78986-25be-549f-b131-67f28f9d8832"}}]}},"pageContext":{}},
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