<\/p>\n
\nAnd God! Don\u2019t we live in interesting times!!!<\/p>\n
Just in the short span of my existence, we have lived thru a number of technological revolutions<\/a>.<\/p>\n [Revolution:<\/em> Not to mention the Sexual Revolution ;\u00a0 )<\/p>\n <\/p>\n \nFirst there was the Computer \/ Digital Revolution<\/a>.<\/p>\n Everything analog became digital, zeros&ones. <\/p>\n \nThen we had the Internet Revolution<\/a>.<\/p>\n It brought the world of knowledge and communication to out fingertips. But for me, I love The Internet so much!!!<\/p>\n I think its the best thing we got since the invention of crunchy bread :\u00a0 )<\/p>\n (And of course, I use secure Tor browsers, spam filters and all such tricks.)<\/p>\n <\/p>\n \nThen the iPhone \/ Smartphone Revolution!<\/a> And their Android sibling.<\/p>\n Well, look around. I hated smartphones at first, refused to have one for longest time.<\/p>\n But now \u2026..<\/p>\n <\/p>\n \nAnd the Social Media Revolution<\/a>.<\/p>\n Well, it brought us the blessings of: Mark Zuckerberg (aka Mr. Facebook), Friendster, Youtube, Instagram, Twitter, Grindr \u2026. and loads of other apps. I honestly don\u2019t want to voice my opinion about that : {<\/p>\n <\/p>\n \nCrypto Currency \/ Blockchain Revolution<\/a><\/p>\n Oh so much hype, oh so much hope of riches beyond imagination! <\/p>\n \nAnd now!!!<\/p>\n The AI Revolution<\/a>.<\/p>\n \u201cAn Invention That Will be the End of All Other Human Inventions\u201d<\/p>\n \u201cOur Final Invention\u201d, written by James Barrat<\/a> in 2013! – already then a clear sighted perspective on things to come.<\/p>\n <\/p>\n <\/p>\n \nNow 10 years later it\u2019s the new gold-rush!<\/p>\n AI Startups are coming out of the woodwork like mushrooms in autumn.<\/p>\n Venture Capital investing billions into the new industry.<\/p>\n And Big Tech Companies as well as Nation States are in a frenzy to get into first position.<\/p>\n The Internet Techno-sphere is ablaze with hype and excitement.<\/p>\n <\/p>\n \nThe AI-thing is still in its Kindergarten state now, the applications more or less something for geeks playing with new toys.<\/p>\n But in reality its no joke.<\/p>\n Because the AI Revolution is on the way.<\/p>\n And like a tsunami it will roll over everything that does not swim.<\/p>\n <\/p>\n \nSO – I tell myself – I better learn to swim, become an expert swimmer in those murky waters ;\u00a0 )<\/span><\/p>\n <\/p>\n \nA good beginning for me is always to get an understanding of the terms and concepts that \u201cthe insiders\u201d are using.<\/p>\n At least a glimpse ;\u00a0 )<\/p>\n <\/p>\n \nEverybody and the grandmother by now has heard of ChatGPT<\/a>, the Chatbot on the internet \u201cwho\u201d can tell you \u201ceverything about everything\u201d and produce poems in the style of Shakespeare and can write computer code and love letters too. Not to forget job applications. Chat GPT – which stands for Chat Generative Pre-trained Transformer<\/a> – is one of the applications using Generative AI models<\/a>.<\/p>\n Generative AI refers to models that generate new content, such as text, images, or audio, based on patterns learned from existing data.<\/p>\n \n1. **Text Generation*<\/span>*: Generative models like GPT-3 and GPT-4 are capable of generating human-like text. They can be used for tasks like content creation, chatbots, language translation, and more.<\/p>\n 2. **Image Generation<\/span>**: Models like DALL\u00b7E and CLIP can generate images from textual descriptions or even from random prompts. They can be used for tasks like art creation, concept visualization, and more.<\/p>\n 3. **Style Transfer<\/span>**: Generative models can be used to apply the style of one image to another, creating visually appealing effects. This is commonly used in art and design.<\/p>\n 4. **Super-Resolution<\/span>**: Models like DeepMind’s WaveNet can generate high-resolution images from lower-resolution inputs. This is used in tasks like upscaling images or improving video quality.<\/p>\n 5. **Face Synthesis<\/span>**: Applications like Deepfake technology use generative models to create realistic-looking images and videos of people that never actually existed. This has both creative and potentially concerning implications.<\/p>\n 6. **Music Composition<\/span>**: Generative models like OpenAI’s MuseNet can compose music in various styles and genres. This can be used for commercial music production and creativity.<\/p>\n 7. **Video Synthesis<\/span>**: Generative models can generate realistic video sequences based on a given input. This has applications in video editing, special effects, and even deepfake videos.<\/p>\n 8. **Anomaly Detection<\/span>**: Generative models can be used to model normal data distributions, allowing them to identify anomalies or outliers. This is useful in fields like fraud detection or quality control.<\/p>\n 9. **Language Translation<\/span>**: Generative models like transformers can be used for tasks like translation, where they generate output text based on input in a different language.<\/p>\n 10. **Content Recommendation<\/span>**: By generating personalized recommendations for users based on their behavior and preferences, generative models can enhance content discovery on platforms like streaming services and e-commerce sites.<\/p>\n 11. **Code Assistance<\/span>**: Like the Github Copilot who can help developers write code more efficiently by providing suggestions and autocompletions based on context. Lately i have been using this thing quite a lot and it turned out quite helpful when i am stuck with some code. Sometimes i use ChatGPT & Co to get a quick overview about an issue or a short summery of a long text. Mostly i use ChatGPT<\/a> and Bard<\/a> and Copilot<\/a> (for code)<\/p>\n <\/div><\/div>\n <\/p>\n The answers seem to be pretty impressive sounding, Just like us – human “experts” – what we sometimes do \ud83d\ude06<\/p>\n <\/p>\n Generative AI ChatBots is just one field of Artificial Intelligence, although the one that gets the most hype and news at the moment. <\/p>\n 1. **Artificial Intelligence (AI):<\/span>** A branch of computer science that focuses on creating machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language understanding.<\/p>\n 2. **Machine Learning:<\/span>** A subset of AI that involves algorithms and statistical models that allow computers to perform a task without being explicitly programmed. Instead, they learn from data and improve their performance over time.<\/p>\n 3. **Deep Learning:<\/span>** A specific type of machine learning that uses neural networks with multiple layers to analyze and learn from large amounts of data. It is particularly effective for tasks like image and speech recognition.<\/p>\n 4. **Neural Network:<\/span>** A computer system inspired by the structure of the human brain, consisting of interconnected nodes (neurons) that process information. They are used in deep learning for tasks like image and speech recognition.<\/p>\n 5. **Algorithm:<\/span>** A step-by-step set of instructions or rules that a computer program follows to perform a specific task or solve a problem.<\/p>\n 6. **Training Data:<\/span>** The data used to train a machine learning model. It’s a set of examples that the model learns from, and it’s crucial for the model’s performance.<\/p>\n 7. **Model:<\/span>** The output or result of a machine learning algorithm after it has been trained on a specific set of data. It’s what the algorithm uses to make predictions or decisions.<\/p>\n 8. **Supervised Learning:<\/em><\/span>** A type of machine learning where the model is trained on labeled data, meaning that the input data is paired with the correct output.<\/p>\n 9. **Unsupervised Learning:<\/span>** A type of machine learning where the model is trained on unlabeled data and must find patterns and relationships within the data on its own.<\/p>\n 10. **Reinforcement Learning:<\/span>** A type of machine learning where an agent learns to make decisions by receiving feedback in the form of rewards or penalties.<\/p>\n 11. **Natural Language Processing (NLP):<\/span>** A field of AI focused on enabling machines to understand, interpret, and generate human language in a way that is valuable and useful.<\/p>\n 12. **Computer Vision:<\/span>** The field of AI that focuses on enabling computers to interpret and understand visual information from the world, including images and videos.<\/p>\n 13. **Chatbot:<\/span>** A computer program designed to simulate human conversation, often used for customer service or providing information.<\/p>\n 14 **Large Language Models (LLMs)<\/span>** Are powerful natural language processing models that are capable of generating human-like text. They are trained on massive datasets and have the ability to generate coherent and contextually appropriate responses to a wide range of prompts. 15. **Bias in AI:<\/span>** When a machine learning model produces results that are systematically skewed in favor of or against a certain group or characteristic.<\/p>\n 16. **Ethical AI:<\/span>** The practice of designing and implementing AI systems in a way that is fair, transparent, and respects ethical principles and values.<\/p>\n These are just some of the basic terms related to AI that can be helpful for non-engineers. <\/div><\/div>\n <\/p>\n All of that is happening right now and some can be, is and will be practically helpful in certain specific areas. All of that – and much more – is happening right now and is developing with exponential speed. Most of the developers, engineers, coders and businessmen (mostly men again! }) seem to be in it for the exciting ride, for the hype and for the money. Only a few of them voice caution.<\/p>\n <\/p>\n But the rapid development of AI have also created a lot of concern and apprehension around the world.<\/p>\n Job displacement and unemployment:<\/strong> AI systems are capable of automating tasks that were previously performed by humans, leading to concerns about job displacement and widespread unemployment. This could have significant social and economic consequences, particularly for those in low-skilled or repetitive jobs.<\/p>\n<\/li>\n Algorithmic bias and discrimination:<\/strong> AI systems are trained on vast amounts of data, which may contain inherent biases and prejudices. If left unchecked, these biases can be perpetuated and amplified by AI algorithms, leading to discriminatory outcomes in areas such as hiring, loan applications, and criminal justice.<\/p>\n<\/li>\n Lack of transparency and explainability:<\/strong> Many AI systems are complex and opaque, making it difficult to understand how they reach their decisions. This lack of transparency can hinder accountability and make it challenging to identify and address potential biases or errors.<\/p>\n<\/li>\n Privacy violations and surveillance concerns:<\/strong> AI systems are increasingly used for data collection, surveillance, and monitoring. This raises concerns about privacy violations and the potential for misuse of personal information.<\/p>\n<\/li>\n Socioeconomic inequality:<\/strong> The benefits of AI may not be evenly distributed, potentially exacerbating existing socioeconomic inequalities. Those with access to AI technologies and the skills to use them may gain an advantage, while those without may be left behind.<\/p>\n<\/li>\n Impact on human decision-making:<\/strong> Over-reliance on AI systems for decision-making can erode human judgment and critical thinking skills. It is important to maintain a balance between AI and human expertise.<\/p>\n<\/li>\n Disinformation and fake content:<\/strong> AI-powered tools can be used to generate and spread misinformation and fake content, making it more difficult to distinguish between fact and fiction. This can have a significant impact on public discourse and decision-making.<\/p>\n<\/li>\n Potential misuse by malicious actors:<\/strong> AI technologies can be misused by malicious actors for cyberattacks, surveillance, or other harmful purposes. It is crucial to develop safeguards and ethical guidelines to prevent such misuse.<\/p>\n<\/li>\n <\/div><\/div>\n <\/p>\n \nAt the other end of the spectrum – opposite the techno-evangelists and gadget-enthusiasts – there are now some influential academics,\u00a0 ethics professors, also some of the early pioneers of AI and recently finally some government regulators who try to hit the breaks of the speeding train.<\/p>\n To rail in the Wild Wild West of AI with a more rational perspective of the future consequences of this revolution.<\/p>\n <\/p>\n \nScience Fiction writers and film makers – naturally – have already written about this for a long time and visualized it all:<\/p>\n The Rise of the Machines<\/a><\/p>\n The AI Apocalypse<\/a><\/p>\n The Singularity<\/a><\/p>\n <\/p>\n The term “singularity” was coined by futurist Ray Kurzweil in his 2005 book The Singularity Is Near<\/a>.<\/p>\n He defines it as “a hypothetical moment in time when technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization.”<\/p>\n In other words, the singularity is the point at which artificial intelligence (AI) becomes so advanced that it surpasses human intelligence and becomes capable of self-improvement. This would lead to an intelligence explosion, with AI becoming increasingly powerful and intelligent at an exponential rate.<\/p>\n There is no consensus on when or if the singularity will occur, but some experts believe it could happen as early as the next few decades. If it does occur, it is likely to have a profound impact on human society, potentially leading to changes that are difficult to even imagine.<\/p>\n Some people believe that the singularity will be a positive development, leading to a utopia in which AI helps to solve all of humanity’s problems. Others are more cautious, and believe that the singularity could pose an existential threat to humanity.<\/p>\n Only time will tell what the true impact of the singularity will be. However, it is a topic that is worth considering, as it could have a profound impact on our future.<\/p>\n Potential benefits of the singularity<\/span><\/p>\n * AI could help to solve some of the world’s most pressing problems, such as climate change, poverty, and disease.<\/p>\n * AI could lead to a new era of economic prosperity and growth.<\/p>\n * AI could help to improve our understanding of the universe and our place in it.<\/p>\n Potential risks of the singularity<\/span><\/p>\n * AI could become so powerful that it poses an existential threat to humanity.<\/p>\n * AI could lead to mass unemployment, as machines become capable of doing many of the jobs that are currently done by humans.<\/p>\n * AI could lead to a loss of privacy, as machines become able to collect and analyze vast amounts of data about our lives.<\/p>\n **What can we do to prepare for the singularity?**<\/p>\n * We need to continue to develop AI in a responsible and ethical manner.<\/p>\n * We need to educate the public about the potential benefits and risks of AI.<\/p>\n * We need to develop safeguards to prevent AI from being used for malicious purposes.<\/p>\n The singularity is a complex and controversial topic, but it is one that we cannot afford to ignore. By understanding the potential benefits and risks of AI, we can take steps to prepare for the future and ensure that the singularity is a positive force for humanity.<\/p>\n (….. says our friend, the ChatGPT AI)<\/p>\n <\/div><\/div>\n <\/p>\n \nMe \u2026.. I personally think that we are heading in this direction. If no Asteroid comes to save our asses from AI ; D<\/p>\n But not in my lifetime, thanks God!<\/p>\n Not thinking too much about AI Singularity, honestly. If I am concerned about anything at all, then it\u2019s about the present day distractions and seductions of a technology that very few specialists actually understand.<\/p>\n Still even the inventor of Neural Networks don\u2019t fully comprehend why \u201cthe thing\u201d is doing what it is doing. <\/p>\n Curiosity kills the cat, they say!<\/p>\n Well, my curiosity drives me to get my hands on The Thing and see if i can make something like a Neural Network myself, a\u00a0 simple Machine Learning application. <\/p>\n Wish me luck!!!!!!!!<\/p>\n I’ll plan to do that in Javascript, which is the easiest language to write code for me. <\/p>\n My idea is to build a very basic Machine Learning application with a simple Neural Network of one hidden layer of neurons (the Black Box) . Like a small child learns to re-cognize simple objects that Mama shows him\/her in a picture book and joyfully points to it and says right word out loud, the application shall recognize and identify a few hand-drawn objects.<\/p>\n \nClock, fish, tree, guitar, pencil, car, house, bicycle ….<\/strong><\/p>\n Seven out of ten times identify the object successfully. This would be nice!<\/p>\n \nI have “trained” this AI-Kid with lots of such simple drawings:<\/p>\n Draw something simple like that and you can see the “synapses” in “his brain” jump and make “intelligent” connections ;\u00a0 )<\/p>\n <\/p>\n
\n– a sudden, radical, or complete change<\/em>
\n– activity or movement designed to effect fundamental changes in the socioeconomic situation<\/em>
\n– a fundamental change in the way of thinking about something\u00a0\u00a0<\/em>
\n– a change of paradigm<\/em>
\n– a changeover in use or preference especially in technology<\/em>
\n]<\/em><\/p>\n
\nIt brought us programming, numerous coding languages, Desktop Publishing, Photoshop and Excel spreadsheets, digital photo-processing and so on.
\nReal Empowerment for normal folks.
\nAllowing us to do lots of things that before have only been the domain of specialists.
\nAnd of course, it brought me my beloved state-of-the-art MacBook Pro, my best & most trusted companion : D<\/p>\n
\nEmail and Wikipedia, Skype, WhatsApp, internet telephone.
\nAlso loads of internet porn, a lot of e-shopping, Amazon.com and the rest.
\nSpam, spam, spam.
\nHacking, tracking, spying, online gambling, the list goes on.
\nLoads of user data, user tracking, online advertisement and such.<\/p>\n
\nEverybody and the grandmother has one.
\nIt made us always online, always available.
\nConvenient! Annoying?
\nIt also brought us endless Selfies and mountains of snapshots that nobody is looking at later on.
\nAnd so on.<\/p>\n
\nNot to mention X.<\/p>\n
\nMoney out of thin air and nobody grocks how this is even possible.
\nSome got pretty rich for sure.
\nAnd \u2026 Oh so much loss and fraud, hacks and crashes too.<\/p>\n![\"\"](\"https:\/\/www.crisrieder.org\/thejourney\/wp-content\/uploads\/2023\/11\/Our_Final_Invention.jpg\")
<\/p>\n
\n\u2026. You just have to ask for it, via text or microphone input.<\/p>\n
\nIt understands the structure of programming languages and can generate code snippets for a wide range of tasks.
\nIt supports languages like Python, JavaScript, Java, C++, and many more.<\/p>\n
\nAnd then, sometimes it just makes up something that does not work at all.
\nJust like me!<\/p>\n
\nTo prevent misinformation or “hallucination” as much as possible:
\n– type the question into several LLM Apps (Large Language Model Apps)
\n– compare the answers, see what makes best sense.
\n– ask for source reverence (if they can provide that.<\/p>\n
\nAnd quick!
\nBut should be taken with a grain of salt, because those Generative AI Bots are known to “hallucinate” more often than not.
\nOr phantasize maybe.
\nThis means they are sometimes simply making things up and telling it with a straight face!!!<\/p>\n
\nOther AI fields are already deeply integrated in out life in applications from Google Search to Self-driving Taxis to medical diagnostics to Marketing to …..
\n…. soon anything i guess \ud83d\ude44<\/p>\n
\nOne prominent example of an LLM is GPT-3 (Generative Pre-trained Transformer 3), which is developed by OpenAI. It is one of the largest publicly available LLMs, with 175 billion parameters. GPT-3 can be used for a variety of tasks, including language translation, content generation, question answering, and more.<\/p>\n
\nIf you have any more specific and detailed questions about any of these terms or would like other information, don’t hesitate to ask ChatGPT<\/a> \ud83d\ude33 !<\/p>\n
\nLike tools, like hammers, like Photoshop\u2026\u2026
\nMany high end computer programs like Microsoft Office or Adobe Photoshop aso. are eager to implement AI features into their already very successful programs.\u00a0
\nWith impressive results, as in the “object detection and deletion” or the “generative fill” in Photoshop.<\/p>\n
\nBecause AI is already now used to improve on AI itself.<\/p>\n
\nAnd a place on the table.
\nProgress for progress sake.<\/span><\/p>\n\n
\nSooner or later people will get there.<\/p>\n
\nAt lest not this singularity.
\n(There is another one<\/a> that i am very interested<\/a> in!)<\/p>\n
\nAnd the bigger The Thing becomes, the deeper the neural networks become, the more of a \u201cBlack Box<\/a>\u201d they become.<\/p>\n
\nSo i can learn – by coding – how such things work.
\nKindergarden Level ;\u00a0 )<\/p>\n
\nReal AI applications are mostly written in Python<\/a> , which is still like Japanese for me\u00a0\ud83d\ude2f\u00a0<\/p>\n
\nAnd visualize the network of connections in some way to see whats going on “inside”\u00a0
\nKind of spying ;\u00a0 D<\/p>\n
\nI hope \ud83d\ude06<\/p>\n![\"\"](\"https:\/\/www.crisrieder.org\/thejourney\/wp-content\/uploads\/2023\/11\/training.jpg\")
<\/p>\n
![\"\"](\"https:\/\/www.crisrieder.org\/thejourney\/wp-content\/uploads\/2023\/11\/neuralNet.jpg\")
<\/a><\/p>\n