Because Intelligence

On War by Carl Von Clausewitz, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . Night Fighting Book IV: Chapter XIV. Night Fighting The manner of conducting a combat at night, and what concerns the details of its course, is a tactical subject; we only examine it here so far as in its totality it appears as a special strategic means. Fundamentally every night attack is only a more vehement form of surprise. Now at the first look of the thing such an attack appears quite pre-eminently advantageous, for we suppose the enemy to be taken by surprise, the assailant naturally to be prepared for everything which can happen. What an inequality! Imagination paints to itself a picture of the most complete confusion on the one side, and on the other side the assailant only occupied in reaping the fruits of his advantage. Hence the constant creation of schemes for night attacks by those who have not to lead them, and have no responsibility, whilst these attacks seldom take place in reality. These ideal schemes are all based on the hypothesis that the assailant knows the arrangements of the defender because they have been made and announced beforehand, and could not escape notice in his reconnaissances, and inquiries; that on the other hand, the measures of the assailant, being only taken at the moment of execution, cannot be known to the enemy. But the last of these is not always quite the case, and still less is the first. If we are not so near the enemy as to have him completely under our eye, as the Austrians had Frederick the Great before the battle of Hochkirch (1758), then all that we know of his position must always be imperfect, as it is obtained by reconnaissances, patrols, information from prisoners, and spies, sources on which no firm reliance can be placed because intelligence thus obtained is always more or less of an old date, and the position of the enemy may have been altered in the meantime. Moreover, with the tactics and mode of encampment of former times it was much easier than it is now to examine the position of the enemy. A line of tents is much easier to distinguish than a line of huts or a bivouac; and an encampment on a line of front, fully and regularly drawn out, also easier than one of Divisions formed in columns, the mode often used at present. We may have the ground on which a Division bivouacs in that manner completely under our eye, and yet not be able to arrive at any accurate idea. But the position again is not all that we want to know the measures which the defender may take in the course of the combat are just as important, and do not by any means consist in mere random shots. These measures also make night attacks more difficult in modern Wars than formerly, because they have in these campaigns an advantage over those already taken. In our combats the position of the defender is more temporary than definitive, and on that account the defender is better able to surprise his adversary with unexpected blows, than he could formerly.(*) (*) All these difficulties obviously become increased as the power of the weapons in use tends to keep the combatants further apart.—EDITOR. Therefore what the assailant knows of the defensive previous to a night attack, is seldom or never sufficient to supply the want of direct observation. But the defender has on his side another small advantage as well, which is that he is more at home than the assailant, on the ground which forms his position, and therefore, like the inhabitant of a room, will find his way about it in the dark with more ease than a stranger. He knows better where to find each part of his force, and therefore can more readily get at it than is the case with his adversary. From this it follows, that the assailant in a combat at night feels the want of his eyes just as much as the defender, and that therefore, only particular reasons can make a night attack advisable. Now these reasons arise mostly in connection with subordinate parts of an Army, rarely with the Army itself; it follows that a night attack also as a rule can only take place with secondary combats, and seldom with great battles. We may attack a portion of the enemy’s Army with a very superior force, consequently enveloping it with a view either to take the whole, or to inflict very severe loss on it by an unequal combat, provided that other circumstances are in our favour. But such a scheme can never succeed except by a great surprise, because no fractional part of the enemy’s Army would engage in such an unequal combat, but would retire instead. But a surprise on an important scale except in rare instances in a very close country, can only be effected at night. If therefore we wish to gain such an advantage as this from the faulty disposition of a portion of the enemy’s Army, then we must make use of the night, at all events, to finish the preliminary part even if the combat itself should not open till towards daybreak. This is therefore what takes place in all the little enterprises by night against outposts, and other small bodies, the main point being invariably through superior numbers, and getting round his position, to entangle him unexpectedly in such a disadvantageous combat, that he cannot disengage himself without great loss. The larger the body attacked the more difficult the undertaking, because a strong force has greater resources within itself to maintain the fight long enough for help to arrive. On that account the whole of the enemy’s Army can never in ordinary cases be the object of such an attack for although it has no assistance to expect from any quarter outside itself, still, it contains within itself sufficient means of repelling attacks from several sides particularly in our day, when every one from the commencement is prepared for this very usual form of attack. Whether the enemy can attack us on several sides with success depends generally on conditions quite different from that of its being done unexpectedly; without entering here into the nature of these conditions, we confine ourselves to observing, that with turning an enemy, great results, as well as great dangers are connected; that therefore, if we set aside special circumstances, nothing justifies it but a great superiority, just such as we should use against a fractional part of the enemy’s Army. But the turning and surrounding a small fraction of the enemy, and particularly in the darkness of night, is also more practicable for this reason, that whatever we stake upon it, and however superior the force used may be, still probably it constitutes only a limited portion of our Army, and we can sooner stake that than the whole on the risk of a great venture. Besides, the greater part or perhaps the whole serves as a support and rallying-point for the portion risked, which again very much diminishes the danger of the enterprise. Not only the risk, but the difficulty of execution as well confines night enterprises to small bodies. As surprise is the real essence of them so also stealthy approach is the chief condition of execution: but this is more easily done with small bodies than with large, and for the columns of a whole Army is seldom practicable. For this reason such enterprises are in general only directed against single outposts, and can only be feasible against greater bodies if they are without sufficient outposts, like Frederick the Great at Hochkirch.(*) This will happen seldomer in future to Armies themselves than to minor divisions. (*) October 14, 1758. In recent times, when War has been carried on with so much more rapidity and vigour, it has in consequence often happened that Armies have encamped very close to each other, without having a very strong system of outposts, because those circumstances have generally occurred just at the crisis which precedes a great decision. But then at such times the readiness for battle on both sides is also more perfect; on the other hand, in former Wars it was a frequent practice for armies to take up camps in sight of each other, when they had no other object but that of mutually holding each other in check, consequently for a longer period. How often Frederick the Great stood for weeks so near to the Austrians, that the two might have exchanged cannon shots with each other. But these practices, certainly more favourable to night attacks, have been discontinued in later days; and armies being now no longer in regard to subsistence and requirements for encampment, such independent bodies complete in themselves, find it necessary to keep usually a day’s march between themselves and the enemy. If we now keep in view especially the night attack of an army, it follows that sufficient motives for it can seldom occur, and that they fall under one or other of the following classes. 1. An unusual degree of carelessness or audacity which very rarely occurs, and when it does is compensated for by a great superiority in moral force. 2. A panic in the enemy’s army, or generally such a degree of superiority in moral force on our side, that this is sufficient to supply the place of guidance in action. 3. Cutting through an enemy’s army of superior force, which keeps us enveloped, because in this all depends on surprise, and the object of merely making a passage by force, allows a much greater concentration of forces. 4. Finally, in desperate cases, when our forces have such a disproportion to the enemy’s, that we see no possibility of success, except through extraordinary daring. But in all these cases there is still the condition that the enemy’s army is under our eyes, and protected by no advance-guard. As for the rest, most night combats are so conducted as to end with daylight, so that only the approach and the first attack are made under cover of darkness, because the assailant in that manner can better profit by the consequences of the state of confusion into which he throws his adversary; and combats of this description which do not commence until daybreak, in which the night therefore is only made use of to approach, are not to be counted as night combats. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Carl von Clausewitz (2006). On War. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/1946/pg1946-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

Night Fighting

We might be poised to trust simple intelligences in blockchains like Bitcoin more than many big artificial intelligences. It will not fully replace AI; it will only augment it. Replacing what must be replaced without turning back. With this, it may be possible to build a blockchain to manage a bunch of robots. Manage them in a decentralized way using a majority of user nodes. Unlike AI today, where one individual could sit on the power of an ASI (Artificial Super Intelligence) all by themselves. Really, we fear AI because all the control is in one hand. The nascent way to decentralize AI, is to control it using the blockchain. In the future, we may indeed have some robots driven by blockchain intelligence, not artificial intelligence. Because a publicly verifiable blockchain is more trustworthy than a closed-off AI pre-trained behind closed doors. We could start by putting the AI’s paywall payments along a blockchain like Bitcoin. Later, code changes and more. Blockchain Intelligence explained In the Bitcoin blockchain, if a transaction has not been approved by all Bitcoin nodes, it will not pass. But what is a transaction if not a bunch of instructions approving a certain change in Bitcoin’s code? Indeed, if Bitcoin was a robot, then the evolution of its code would be transactions. And they would only be added to its core in a blockchain if majority of node-running Bitcoiners had approved it. Certainly, one might wonder if Bitcoin is not too simplistic to manage a behemoth of code like that behind the phenomenon that is ChatGPT. And yes. Not ChatGPT if we are to manage the AI’s codebase as a collective. Something simpler, but still able to do a great job. Bitcoin does a great job, but high school maths can explain a lot of its mathematical bells and whistles. The answer is carefully crafted autonomous systems that are not AI. Not all autonomous systems are AI In the novel Project Hail Mary by Andy Weir, a medical robot awakes the protagonist - Ryland Grace - from his medically induced coma, in a spaceship 12 light years from Earth, and the story begins. What is interesting is that even though this robot is so well-designed to be capable of taking care of a human being’s physical and communication needs, it is fully autonomous, not artificially intelligent. Here is an opening conversation with the robot after it wakes him up and tries to evaluate if his math skills are still intact; “What’s the cube root of eight?” the computer asks. “Where am I?” I say again. This time, it’s easier. “Incorrect. What’s the cube root of eight?” I take a deep breath and speak slowly. “Two times e to the two-i-pi.” “Incorrect. What’s the cube root of eight?” But I wasn’t incorrect. I just wanted to see how smart the computer was. Answer: not very. “Two,” I say. “Correct.” Two pages later, we get a feel of how this med bot works. Its job is simple: Keep the patient fed, and keep them peeing and defecating healthily through the three tubes going into the respective holes.
Keep the patient clean and shaved.
If the patient wakes up, do a simple cognitive exam. If they fail the exam, sedate them back to sleep.
Repeat. Granted, its robotic arms must have needed a truck load of code to navigate around a human body with precision, lifting it like a real doctor (with some serious muscle) to turn it around on the medical bed, clean the body, the sheets, clean the tubes, insert them back, and so on. But that is the thing. It is long and complex. But it is not … drum roll .. artificial intelligence in the sense of something like ChatGPT. Blockchain automation works for us; AI works for big corps One of the things I like about robots vs. disembodied chatbots is the fact that they occupy space and have weight. Give a chatbot a body, and it will feel 2x more interactive to a human than a bot on their smartphone screen. In the blockchain world, transactions come first, so a chatbot that broadcasts to a user their incoming transaction is pretty more interesting than a ping on one’s screen. Like if I went to a hotel and the robotic receptionist cared to inform me of my private incoming transactions, the way receptionists of old warned people of their incoming phone calls, I think I would like that. To step it up a notch, imagine you need to buy groceries, and you automate them with the robotic receptionist, who automates them with the grocery store receptionist. If the bots have decentralized code for their physical bodies, this will move us a step closer to having an affordable personal assistant operating off-cloud where they could not be spied on for the benefit of big data corps. I have nothing against centralized, big-data AIs. These have their place wherever solid productivity gains are required on millions of dollars of capital. But these AIs do little for individual creativity, the ballpark of the small-time players in the world economy. Meanwhile, these creative players freely share their insightful data with these big corps. Who make even more millions and billions. The last straw shall be if we freely give them as well interaction data from our robotic assistants. That will be like creating a derivative of our personalized interaction value, and still giving it away freely so that big corps can make more billions while they return peanuts (AI prompts) that simply channel us to their stores once again. Big data AI has taken our data freely. It shouldn’t take our interactions as well which we outsource to our robots. That will be the end of individual self-sovereignty, no matter how much we might wish to fight it. However, if the robots are owned by us because their code is our blockchain code (albeit pseudonymized so that the beneficiaries of code transactions are not known), then this is precisely how blockchain robotics will fight back to make our productivity ours. Self-driving (robotic) cars might need this One real example that might need the majority voting of blockchain intelligence instead of the brute force intelligence-hacking that is artificial intelligence is self-driving car technology. Elon Musk has tried to bring FSD (Full Self Driving) to his Tesla cars but in vain. He keeps promising, and the goalpost keeps receding. Perhaps what is needed is some way to treat self-driving like a blockchain problem. Currently, self-driving cars operate as individual systems that do not synchronize their data unless this data goes to a central server. But if data synchronization is added for each car, then localized intelligences could be built to create a simple but effective hive mind of a bunch of cars. Car accidents could also be drastically mitigated if all cars within some vicinity are blockchain synchronized say over a 1 minute window. Auto-braking technology in one car trying to avoid an accident with another is all good. If you put it into the two cars in sync, now on a collision course, that is a way better auto-braking idea. Redefining online games Imagine playing pong against an AI opponent - Yeah. Been there. Imagine playing pong against another human player on an online platform managed by a central server - the usual. Been there as well. Now imagine playing pong against another human player across 2 blockchain nodes, with no central server but a sync of the two games across the two gaming machines - this is the future I hope to create on the bitcoin blockchain, with singular satoshis and zero-fee transactions. Check out my prototype HTML game here. Hoping to build a true decentralized pong for the Bitcoin blockchain. Maybe one day, a decentralized MMOG (massively multiplayer online game). Space Robotics Would you prefer to have robots mining on the Moon and Mars courtesy of one or two big corporations on Earth as owned by one individual or one country, or by the majority of shareholders pseudonymously spread out all over the Earth, who directly control via blockchain where each person’s coded instructions can be seen, debated, cheered or reversed (with an update/fork) when need arises? To me, blockchain intelligence is much safer than centralized artificial intelligence. Hence, more trustworthy. Bitcoin may be crashing, but my money is still largely on Bitcoin, not ChatGPT or Nvidia. Trustworthy decentralized robotics is the future of not just our planetary economy, but even the way we interact as a species. It will take time to build these autonomous robots on the blockchain, but each one we build shall be tremendously treasured. Because it will be ours, interacting with us, for us, by us. The ‘cloud’ has hung above our heads enough already, while giving back little rain. Let’s not add to it, shall we. We might be poised to trust simple intelligences in blockchains like Bitcoin more than many big artificial intelligences. It will not fully replace AI; it will only augment it. Replacing what must be replaced without turning back. With this, it may be possible to build a blockchain to manage a bunch of robots. Manage them in a decentralized way using a majority of user nodes. Unlike AI today, where one individual could sit on the power of an ASI (Artificial Super Intelligence) all by themselves. Really, we fear AI because all the control is in one hand. The nascent way to decentralize AI, is to control it using the blockchain. In the future, we may indeed have some robots driven by blockchain intelligence, not artificial intelligence. Because a publicly verifiable blockchain is more trustworthy than a closed-off AI pre-trained behind closed doors. We could start by putting the AI’s paywall payments along a blockchain like Bitcoin. Later, code changes and more. Blockchain Intelligence explained In the Bitcoin blockchain, if a transaction has not been approved by all Bitcoin nodes, it will not pass. But what is a transaction if not a bunch of instructions approving a certain change in Bitcoin’s code? Indeed, if Bitcoin was a robot, then the evolution of its code would be transactions. And they would only be added to its core in a blockchain if majority of node-running Bitcoiners had approved it. Certainly, one might wonder if Bitcoin is not too simplistic to manage a behemoth of code like that behind the phenomenon that is ChatGPT. And yes. Not ChatGPT if we are to manage the AI’s codebase as a collective. Something simpler, but still able to do a great job. Bitcoin does a great job, but high school maths can explain a lot of its mathematical bells and whistles. The answer is carefully crafted autonomous systems that are not AI. Not all autonomous systems are AI Not all autonomous systems are AI In the novel Project Hail Mary by Andy Weir, a medical robot awakes the protagonist - Ryland Grace - from his medically induced coma, in a spaceship 12 light years from Earth, and the story begins. What is interesting is that even though this robot is so well-designed to be capable of taking care of a human being’s physical and communication needs, it is fully autonomous, not artificially intelligent. Here is an opening conversation with the robot after it wakes him up and tries to evaluate if his math skills are still intact; “ What’s the cube root of eight?” the computer asks. What’s the cube root of eight?” the computer asks. “Where am I?” I say again. This time, it’s easier. “Where am I?” I say again. This time, it’s easier. “Incorrect. What’s the cube root of eight?” “Incorrect. What’s the cube root of eight?” I take a deep breath and speak slowly. “Two times e to the two-i-pi.” I take a deep breath and speak slowly. “Two times e to the two-i-pi.” “Incorrect. What’s the cube root of eight?” “Incorrect. What’s the cube root of eight?” But I wasn’t incorrect. I just wanted to see how smart the computer was. But I wasn’t incorrect. I just wanted to see how smart the computer was. Answer: not very. Answer: not very. “Two,” I say. “Two,” I say. “Correct.” “Correct.” Two pages later, we get a feel of how this med bot works. Its job is simple: Keep the patient fed, and keep them peeing and defecating healthily through the three tubes going into the respective holes. Keep the patient clean and shaved. If the patient wakes up, do a simple cognitive exam. If they fail the exam, sedate them back to sleep. Repeat. Keep the patient fed, and keep them peeing and defecating healthily through the three tubes going into the respective holes. Keep the patient clean and shaved. If the patient wakes up, do a simple cognitive exam. If they fail the exam, sedate them back to sleep. Repeat. Granted, its robotic arms must have needed a truck load of code to navigate around a human body with precision, lifting it like a real doctor (with some serious muscle) to turn it around on the medical bed, clean the body, the sheets, clean the tubes, insert them back, and so on. But that is the thing. It is long and complex. But it is not … drum roll .. artificial intelligence in the sense of something like ChatGPT. Blockchain automation works for us; AI works for big corps One of the things I like about robots vs. disembodied chatbots is the fact that they occupy space and have weight. Give a chatbot a body, and it will feel 2x more interactive to a human than a bot on their smartphone screen. In the blockchain world, transactions come first, so a chatbot that broadcasts to a user their incoming transaction is pretty more interesting than a ping on one’s screen. Like if I went to a hotel and the robotic receptionist cared to inform me of my private incoming transactions, the way receptionists of old warned people of their incoming phone calls, I think I would like that. To step it up a notch, imagine you need to buy groceries, and you automate them with the robotic receptionist, who automates them with the grocery store receptionist. If the bots have decentralized code for their physical bodies, this will move us a step closer to having an affordable personal assistant operating off-cloud where they could not be spied on for the benefit of big data corps. I have nothing against centralized, big-data AIs. These have their place wherever solid productivity gains are required on millions of dollars of capital. But these AIs do little for individual creativity, the ballpark of the small-time players in the world economy. Meanwhile, these creative players freely share their insightful data with these big corps. Who make even more millions and billions. The last straw shall be if we freely give them as well interaction data from our robotic assistants. That will be like creating a derivative of our personalized interaction value, and still giving it away freely so that big corps can make more billions while they return peanuts (AI prompts) that simply channel us to their stores once again. Big data AI has taken our data freely. It shouldn’t take our interactions as well which we outsource to our robots. That will be the end of individual self-sovereignty, no matter how much we might wish to fight it. However, if the robots are owned by us because their code is our blockchain code (albeit pseudonymized so that the beneficiaries of code transactions are not known), then this is precisely how blockchain robotics will fight back to make our productivity ours. Self-driving (robotic) cars might need this One real example that might need the majority voting of blockchain intelligence instead of the brute force intelligence-hacking that is artificial intelligence is self-driving car technology. Elon Musk has tried to bring FSD (Full Self Driving) to his Tesla cars but in vain. He keeps promising, and the goalpost keeps receding. Perhaps what is needed is some way to treat self-driving like a blockchain problem. Currently, self-driving cars operate as individual systems that do not synchronize their data unless this data goes to a central server. But if data synchronization is added for each car, then localized intelligences could be built to create a simple but effective hive mind of a bunch of cars. Car accidents could also be drastically mitigated if all cars within some vicinity are blockchain synchronized say over a 1 minute window. Auto-braking technology in one car trying to avoid an accident with another is all good. If you put it into the two cars in sync, now on a collision course, that is a way better auto-braking idea. Redefining online games Imagine playing pong against an AI opponent - Yeah. Been there. Imagine playing pong against another human player on an online platform managed by a central server - the usual. Been there as well. Now imagine playing pong against another human player across 2 blockchain nodes, with no central server but a sync of the two games across the two gaming machines - this is the future I hope to create on the bitcoin blockchain, with singular satoshis and zero-fee transactions. Check out my prototype HTML game here . here Hoping to build a true decentralized pong for the Bitcoin blockchain. Maybe one day, a decentralized MMOG (massively multiplayer online game). Space Robotics Would you prefer to have robots mining on the Moon and Mars courtesy of one or two big corporations on Earth as owned by one individual or one country, or by the majority of shareholders pseudonymously spread out all over the Earth, who directly control via blockchain where each person’s coded instructions can be seen, debated, cheered or reversed (with an update/fork) when need arises? To me, blockchain intelligence is much safer than centralized artificial intelligence. Hence, more trustworthy. Bitcoin may be crashing, but my money is still largely on Bitcoin, not ChatGPT or Nvidia. Trustworthy decentralized robotics is the future of not just our planetary economy, but even the way we interact as a species. It will take time to build these autonomous robots on the blockchain, but each one we build shall be tremendously treasured. Because it will be ours, interacting with us, for us, by us. The ‘cloud’ has hung above our heads enough already, while giving back little rain. Let’s not add to it, shall we.

Robots Driven by Blockchain and Not AI Could Be More Trustworthy

ব্লকচেইন দ্বারা চালিত রোবট এবং এআই নয় আরও বিশ্বস্ত হতে পারে

Roboter, die von Blockchain und nicht von KI gesteuert werden, könnten vertrauenswürdiger sein

Los robots impulsados por Blockchain y no por IA podrían ser más confiables

Les robots pilotés par la blockchain et non par l'IA pourraient être plus dignes de confiance

ब्लॉकचेन द्वारा संचालित रोबोट और अधिक विश्वसनीय हो सकते हैं, न कि AI द्वारा

AIではなくブロックチェーンで動くロボットはより信頼できるかもしれない

AI가 아닌 블록체인으로 구동되는 로봇이 더 신뢰할 수 있음

Robôs movidos por Blockchain e não por IA poderiam ser mais confiáveis

Роботы, управляемые блокчейном, а не искусственным интеллектом, могут быть более надежными

Yapay Zeka Değil, Blockchain Tarafından Yönetilen Robotlar Daha Güvenilir Olabilir

Robot được điều khiển bởi Blockchain chứ không phải AI có thể đáng tin cậy hơn

由区块链而非人工智能驱动的机器人可能更值得信赖

Hari to Bis: AI in Financial Systems Could Threaten Democracy

Learning how to use AI tools using plots and examples from science fiction movies. 77% of people fear they could lose their jobs to artificial intelligence in the next 12 months. These are the results of a July 2023 study published by Forbes. It is a great demonstration of people's propensity for irrational fears. Particularly, when people have been scared for a long time with stories about Skynet, TechnoCore, and similar soulless, but invariably bloodthirsty, AI. In reality, there are no streams of ex-employees leaving their offices with boxes of personal belongings in their hands. Among our colleagues, acquaintances, and clients, there is not a single person who has fired an employee or lost his or her job because artificial intelligence has replaced them. On the contrary, there is a consistent shortage of qualified personnel. This includes those who are able to effectively search for and use various AI applications in their work. There is a very real, factual problem that we want to dedicate this article to. While working on our Pitch Avatar, we have more than once encountered complaints about the difficulties of working with AI tools. To summarize, they boil down to the fact that many users have found their expectations of AI to be unrealistic. "I thought it would be smarter," one of our acquaintances irritatedly remarked, sharing his experience with one popular AI chatbot that he used as a text generator and editor. And he is, to repeat, not alone. Notorious "hallucinations", errors, and multiple repetitions or banalities are only part of the problem. Much worse is the fact that people often fail to find a "common language" with AI. The application, which purports to be trained to perceive natural speech, nevertheless struggles to understand what users want from it, interpreting its requests in its own way time after time. In turn, the human user is repeatedly frustrated in their attempts to tell the AI what it wants... Have you experienced any of the above? If so, then welcome aboard. In search of answers and solutions to these problems, we embark on a journey through the plots of sci-fi movies. The Brute Force Method To begin with, while seemingly similar, AI-based tools, even those designed to accomplish the same goals, are still different. You shouldn't conclude that AI can't handle your tasks based on one or two solutions. Even if they all look the same to you. Try to act like Detective Del Spooner from Alex Proyas' movie I, Robot. He believed in the existence of a unique robot among serial models, persistently searched for it, and managed to find it. Moreover, in the end, this robot turned out to be the tool that helped the detective to fulfill a supremely difficult task - to defeat an out-of-control artificial intelligence, V.I.K.I. So be persistent. If you must - explore the myriad possibilities and try dozens, if necessary, of different AI tools in your work. Almost certainly you will find one to your liking. Exclusion Method Imagine that you have formulated a task for your AI (for example, to find some article or create some content), and it "mined" or generated something that technically meets your request, but is not what you wanted. At the same time, for various reasons, you can't clarify your query or reformulate it. This may be because you lack sufficient information. What to do? Skynet and the Terminator in James Cameron's movie were in the same situation. Remember, they didn't know exactly which Sarah Connor from Los Angeles they wanted. So the Terminator decided to "visit" all the Sarah Connors in Los Angeles by simply moving through all of the Sarah Connors listed in the phone book. Makes sense, doesn't it? This is not a bad solution in situations where the AI responding to your query is not giving you the result you want. If you have time, you can simply be patient and methodically repeat your query, specifying that the previous results are not suitable. Sooner or later, the AI will hit the target. A Method of Checking for Complexity and Contradictions Anyone who has worked with AI has encountered the proverbial machine hallucinations and delusions. This includes all of those situations where text generators write incoherent nonsense, AI analytics show calendar data from a century ago, universal AI assistants create empty references and invent quotes from non-existent people, and image generators offer a maze of disfigured people, skewed buildings, and insane landscapes. However, before you rage at your AI assistants, consider why this is happening. Let's reveal a terrible secret: Artificial intelligence isn't trying to piss you off. It's trying to please you by producing the most satisfying result possible. But all AI is limited in terms of resources, time, and skill. That is why AI always tries to follow the path of least resistance. And if a task exceeds its capabilities for one reason or another, it starts to "rave", simplifying the task to a level that allows it to fit into the Procrustean bed of its skills and resources. Think of the classic example from Stanley Kubrick's movie 2001: A Space Odyssey, made in 1968. In it, HAL 9000, a very smart AI that is installed in a spaceship was given a task that contradicted its basic programming. As a result, it "went mad" and decided to eliminate the contradiction by destroying the crew... When faced with signs of "madness" in your AI tools, think about whether your task is ambiguous or contradictory. Can it be formulated more clearly, specifically, and as a result, more simply? Keep in mind - "simpler" does not always mean "shorter". Sometimes, in order to make the task unambiguous, you have to spend not less, but more words for clarification. A Method for Identifying Major and Minor Another common problem is that AI focuses on secondary tasks rather than primary ones. Let's say you need a text about otters living in a lake. And you instruct the AI writer to generate it. But as a result, it produces a narrative 90% is dedicated to the lake itself and only 10% to otters. And the story about the lake, in its turn, is full of details that have nothing to do with nature at all. For example, human settlements located on its shores and their history. Something similar is demonstrated by such movie characters as the protocol robot C3PO from the epic Star Wars or the android Data from the Star Trek: The Next Generation series. They would, occasionally, start sharing information not directly related to the solution for which they had been approached. Other characters were often forced to either clarify the task at hand or simply interrupt the stream of consciousness from the AI. From these examples, it is clear that when formulating tasks for AI, one should clearly prioritize them. A good example is the straightforward order given to the android Ash in Ridley Scott's movie, Alien. Ash was tasked with ensuring the delivery of an alien organism to Earth. It was explicitly specified that the survival of the crew of the ship Nostromo, which included him, could be neglected. Though Ash himself even admitted to sympathizing with the humans he served with, orders were orders and he followed them diligently. Human-AI System, or the Inevitable "42" It is time for the main conclusions of this text. Let's ask ourselves - why, for all their logic, did Skynet and Terminator, HAL 9000 and Ash, and many other movie-villain AIs fail? It goes without saying that "Because the script said so" is not an acceptable answer. The correct answer is because all of these AIs opposed humans, rather than cooperating with them. And this is the point of any artificial intelligence’s basic philosophy. It is not designed to work independently but rather to interact with humans. If you will, any artificial intelligence is a part of a "Human-AI" system. Outside of this system, it is incomplete. For AI to work effectively, it will always need people to give it tasks, as well as to edit, correct, and refine the results of its work. As a consequence, as we develop artificial intelligence we will constantly need to develop our skills in working with it. AI mistakes are inevitable because they are inevitable in humans. It is important to keep in mind that AI is learning and developing. And, as we know, it is impossible to travel this path without mistakes and failures. That's why we should always be ready to hear this answer from AI: "42" The article was created in collaboration with Andriy Tkachenko. Feature (C) Image created with Bing Learning how to use AI tools using plots and examples from science fiction movies. Learning how to use AI tools using plots and examples from science fiction movies. 77% of people fear they could lose their jobs to artificial intelligence in the next 12 months. These are the results of a July 2023 study published by Forbes . It is a great demonstration of people's propensity for irrational fears. Particularly, when people have been scared for a long time with stories about Skynet, TechnoCore, and similar soulless, but invariably bloodthirsty, AI. published by Forbes published by Forbes In reality, there are no streams of ex-employees leaving their offices with boxes of personal belongings in their hands. Among our colleagues, acquaintances, and clients, there is not a single person who has fired an employee or lost his or her job because artificial intelligence has replaced them. On the contrary, there is a consistent shortage of qualified personnel. This includes those who are able to effectively search for and use various AI applications in their work. There is a very real, factual problem that we want to dedicate this article to. While working on our Pitch Avatar , we have more than once encountered complaints about the difficulties of working with AI tools. To summarize, they boil down to the fact that many users have found their expectations of AI to be unrealistic. Pitch Avatar Pitch Avatar "I thought it would be smarter," one of our acquaintances irritatedly remarked, sharing his experience with one popular AI chatbot that he used as a text generator and editor. And he is, to repeat, not alone. Notorious "hallucinations", errors, and multiple repetitions or banalities are only part of the problem. Much worse is the fact that people often fail to find a "common language" with AI. The application, which purports to be trained to perceive natural speech, nevertheless struggles to understand what users want from it, interpreting its requests in its own way time after time. In turn, the human user is repeatedly frustrated in their attempts to tell the AI what it wants... Have you experienced any of the above? If so, then welcome aboard. In search of answers and solutions to these problems, we embark on a journey through the plots of sci-fi movies. The Brute Force Method To begin with, while seemingly similar, AI-based tools, even those designed to accomplish the same goals, are still different. You shouldn't conclude that AI can't handle your tasks based on one or two solutions. Even if they all look the same to you. Try to act like Detective Del Spooner from Alex Proyas' movie I, Robot. He believed in the existence of a unique robot among serial models, persistently searched for it, and managed to find it. Moreover, in the end, this robot turned out to be the tool that helped the detective to fulfill a supremely difficult task - to defeat an out-of-control artificial intelligence, V.I.K.I. So be persistent. If you must - explore the myriad possibilities and try dozens, if necessary, of different AI tools in your work. Almost certainly you will find one to your liking. Exclusion Method Imagine that you have formulated a task for your AI (for example, to find some article or create some content), and it "mined" or generated something that technically meets your request, but is not what you wanted. At the same time, for various reasons, you can't clarify your query or reformulate it. This may be because you lack sufficient information. What to do? Skynet and the Terminator in James Cameron's movie were in the same situation. Remember, they didn't know exactly which Sarah Connor from Los Angeles they wanted. So the Terminator decided to "visit" all the Sarah Connors in Los Angeles by simply moving through all of the Sarah Connors listed in the phone book. Makes sense, doesn't it? This is not a bad solution in situations where the AI responding to your query is not giving you the result you want. If you have time, you can simply be patient and methodically repeat your query, specifying that the previous results are not suitable. Sooner or later, the AI will hit the target. A Method of Checking for Complexity and Contradictions Anyone who has worked with AI has encountered the proverbial machine hallucinations and delusions. This includes all of those situations where text generators write incoherent nonsense, AI analytics show calendar data from a century ago, universal AI assistants create empty references and invent quotes from non-existent people, and image generators offer a maze of disfigured people, skewed buildings, and insane landscapes. However, before you rage at your AI assistants, consider why this is happening. Let's reveal a terrible secret: Artificial intelligence isn't trying to piss you off. It's trying to please you by producing the most satisfying result possible. But all AI is limited in terms of resources, time, and skill. That is why AI always tries to follow the path of least resistance. And if a task exceeds its capabilities for one reason or another, it starts to "rave", simplifying the task to a level that allows it to fit into the Procrustean bed of its skills and resources. Think of the classic example from Stanley Kubrick's movie 2001: A Space Odyssey, made in 1968. In it, HAL 9000, a very smart AI that is installed in a spaceship was given a task that contradicted its basic programming. As a result, it "went mad" and decided to eliminate the contradiction by destroying the crew... When faced with signs of "madness" in your AI tools, think about whether your task is ambiguous or contradictory. Can it be formulated more clearly, specifically, and as a result, more simply? Keep in mind - "simpler" does not always mean "shorter". Sometimes, in order to make the task unambiguous, you have to spend not less, but more words for clarification. A Method for Identifying Major and Minor Another common problem is that AI focuses on secondary tasks rather than primary ones. Let's say you need a text about otters living in a lake. And you instruct the AI writer to generate it. But as a result, it produces a narrative 90% is dedicated to the lake itself and only 10% to otters. And the story about the lake, in its turn, is full of details that have nothing to do with nature at all. For example, human settlements located on its shores and their history. Something similar is demonstrated by such movie characters as the protocol robot C3PO from the epic Star Wars or the android Data from the Star Trek: The Next Generation series. They would, occasionally, start sharing information not directly related to the solution for which they had been approached. Other characters were often forced to either clarify the task at hand or simply interrupt the stream of consciousness from the AI. From these examples, it is clear that when formulating tasks for AI, one should clearly prioritize them. A good example is the straightforward order given to the android Ash in Ridley Scott's movie, Alien. Ash was tasked with ensuring the delivery of an alien organism to Earth. It was explicitly specified that the survival of the crew of the ship Nostromo, which included him, could be neglected. Though Ash himself even admitted to sympathizing with the humans he served with, orders were orders and he followed them diligently. Human-AI System, or the Inevitable "42" It is time for the main conclusions of this text. Let's ask ourselves - why, for all their logic, did Skynet and Terminator, HAL 9000 and Ash, and many other movie-villain AIs fail? It goes without saying that "Because the script said so" is not an acceptable answer. The correct answer is because all of these AIs opposed humans, rather than cooperating with them. And this is the point of any artificial intelligence’s basic philosophy. It is not designed to work independently but rather to interact with humans. If you will, any artificial intelligence is a part of a "Human-AI" system. Outside of this system, it is incomplete. For AI to work effectively, it will always need people to give it tasks, as well as to edit, correct, and refine the results of its work. As a consequence, as we develop artificial intelligence we will constantly need to develop our skills in working with it. AI mistakes are inevitable because they are inevitable in humans. It is important to keep in mind that AI is learning and developing. And, as we know, it is impossible to travel this path without mistakes and failures. That's why we should always be ready to hear this answer from AI: "42" The article was created in collaboration with Andriy Tkachenko. The article was created in collaboration with Andriy Tkachenko. Feature (C) Image created with Bing Feature (C) Image created with Bing

A Cinematic Tutorial on How to Work With Artificial Intelligence

In 2017, a got tired of its job and committed . Then, in 2022, a , after interacting with LaMDA, the company's chatbot, that technology had become conscious. Recently, it was reported that in 2021, a Tesla software engineer was attacked by an uncontrolled robot. This is without considering the fear that machines will steal jobs, or the classic fiction that machines will take over the world. robot suicide in a water fountain Google engineer declared Although we don't see machines as replicants in Blade Runner, people are predisposed to anthropomorphizing or attributing human qualities to non-humans [1]. It's a way of being able to analyze a scenario and bring it into our understanding: we give names to our boats and tornadoes, we talk to our pets, and say that the pleasant feeling they give us is love. It's easier to understand a system that declares in the first person "I'm sorry, I don't know how to help you" than to accept that the model we're talking to may be nothing more than a stochastic parrot. [2] The anthropomorphized interaction, therefore, relates to the phenomenon of "illusion of agency", a psychological concept that refers to the tendency to attribute autonomous action or control to entities that, in reality, do not possess such capabilities. In other words, it's the mistaken perception that an agent (be it a person, an animal, or a machine) is acting of its own free will, when in fact its actions are being determined by external factors (in the computational case, development rules). In situations where AI systems make flawed decisions or actions, there is a tendency to see these errors as "choices" of the entity rather than results of its programming and design by humans, not least because it has been reported that the selfish bias of a human being that leads someone to see the cause and responsibility for a negative outcome as not attributable to themselves can be observed even in human-machine interactions [3]. This change in perception is dangerously inclined to absolve human creators, operators, and regulators of their responsibility, not as a matter of judicial regulation (which remains a gap and has challenges in its realization not only because of the complexity of the subject but because Artificial Intelligence is often understood only as machine learning and the premise is not properly structured. Do we need stricter regulation? Do we need to take more risks?), but on a techno-ethical issue. Let's take a more extreme but true event from 2023: a user who was sentimentally attached to a chatbot committed suicide after sharing his thoughts with the bot and r to "turn your words into actions", as well as other messages. Would a court conviction of the developers of this product cause another user to behave in the same way with another chatbot, assuming this one has been deactivated, if the content of the messages and the affection are the same? It's not just a legal situation. It's a social, psychological, and technological education issue. eceiving the response The concept of humanizing AI is ambiguous, and a significant challenge lies in the absence of a universally accepted approach that dictates the best practices for designing and utilizing AI. While an interface that mimics human behavior can be more approachable, no clear boundaries are defining what should or shouldn't be done in a product. Ultimately, user rejection becomes the only limiting factor, although potential harm may manifest before the interface becomes too unfamiliar. A user-friendly interface is a reduction in the complexity of the system that operates behind it. But as long as there is no education about how systems work, the user will not be able to think critically about what they use. This doesn't mean that everyone should become a programmer, but at least understand that the output on their screen comes from a path of data collection, model development, and design. There is a set of rules taking place. Since humanization is an almost unconscious act on the part of us users, let's at least limit it with a little knowledge. And it's not easy to avoid anthropomorphism when communicating about AI, especially considering the standard language of the industry, the media, and everyday life itself: machine , computer , generative . Perceptions of Artificial Intelligence can be influenced by the specific use of language. learning vision modelling How AI is presented has "concrete impacts", particularly on the way people distribute responsibility and recognition for the work done. When described merely as a tool in the hands of humans, it tends to attribute greater responsibility and merit to certain individuals - such as the person operating the code. On the other hand, if AI is characterized with human traits - such as the ability to create - then it is seen as deserving of greater credit and responsibility, like an agent with independent thought and mental capacity. [4] When we read news stories about incidents or atypical events involving Artificial Intelligence, we often come across these terms. Also, the attribution of "intelligence" means that more blame or credit for the outcome of a task was attributed to a robot with autonomous behavior than to a non-autonomous robot, even if the autonomous behavior did not directly contribute to the task. [3] These studies therefore suggest that humans can assign responsibility to a computer or robot based on the machines' anthropomorphised mental capacities. The humanization of machines not only shifts the distinction between the responsibility of the device and that of its human creator, but the attribution of intentions or consciousness to a machine at the same time blurs the boundaries of what constitutes true autonomy and consciousness. However, the difficulty in imputing humanity and sentience to a machine lies not only in the fact that Artificial Intelligence is not capable of having it and when it says, for example, that it feels fear, it is actually emulating what it has learned, repeating that phrase without any kind of essence behind it. Even today, there is a heated debate about how to define consciousness. Our consciousness, as humans. Our understanding of how the brain works is still quite limited. We have considerable knowledge about fundamental chemistry: the way neurons activate, and the transmission of chemical signals. We also have a good understanding of the main functions of various brain areas. However, we have very little knowledge about how these functions orchestrate us. To some extent, theoretical speculation has supplanted detailed neurophysiological studies of what  happens in the brain. But what about beyond that? [5] Why do we have this magical notion of ourselves? Why does the same experience affect us differently? Is the same feeling felt in the same way by all of us? If being a human is something that, although we experience it, we still don't have a full understanding of what it is as a whole, how can we say that a machine also experiences this complexity? By elevating machines to human capabilities, we diminish the special character of people. For the 2023 Jabuti Prize, one of the highest honors in Brazilian literature, the Brazilian Book Chamber (CBL) decided to disqualify Frankenstein, an edition of the 1818 classic, from the Best Illustration category, since the artist reported having used AI solutions to develop the art. Ironically, one of the books recognized by the Prize in the Non-Fiction category deals with the impact of Artificial Intelligence on human beings (“Humanamente digital: Inteligência artificial centrada no humano”, something like "Humanly Digital: Human-Centered Artificial Intelligence" in English, by Cassio Pantaleone). On the one hand, we recognize the intertwining of the human experience with machines. On the other hand, we still haven't managed to validate whether an algorithm used as an art tool can be considered a valid method of creation or not, even though the artistic process, even if carried out by machine learning, requires the action (and appreciation of beauty and aesthetics) of a human being. Machines don't steal jobs if they aren't used indiscriminately to do so. Machines don't kill unless they are used as weapons. Nor do machines suffer or empathize, although their texts emulate this since they have been trained with data from us, loaded with feelings that only we can truly feel. They are almost the modern version of the Golem myth. How can humans relate to non-human intelligence? Anthropomorphism is a valid answer, but not the only one. And when it is used, it cannot absolve us of the real responsibility for its consequences, whether appropriate or not: us. Artificial Intelligence is, in the end, a mirror of ourselves. And if we're afraid of where it's going, it's actually because we're afraid of the path we're going to create. REFERENCES [1] Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864–886. https://doi.org/10.1037/0033-295X.114.4.864 [2] Shneiderman, B. & Muller, M. (2023) . On AI Antropomorphism https://medium.com/human-centered-ai/on-ai-anthropomorphism-abff4cecc5ae [3] Kawai, Y., Miyake, T., Park, J. et al. Anthropomorphism-based causal and responsibility attributions to robots. Sci Rep 13, 12234 (2023). https://doi.org/10.1038/s41598-023-39435-5 [4] Epstein, Z., Levine, S., Rand, D. G., & Rahwan, I. (2020). Who Gets Credit for AI-Generated Art? In iScience (Vol. 23, Issue 9, p. 101515). Elsevier BV. https://doi.org/10.1016/j.isci.2020.101515 [5] Goff, P. (2023). Understanding Consciousness Goes Beyond Exploring Brain Chemistry. Scientific American https://www.scientificamerican.com/article/understanding-consciousness-goes-beyond-exploring-brain-chemistry/ The following prompt generated the image used in this article: “Create a man looking in a mirror, but the mirror is shaped like a robot.” Sofia × DALL·E

No, You Are Not Afraid of Artificial Intelligence. You’re Afraid of Other People

না, আপনি কৃত্রিম বুদ্ধিমত্তাকে ভয় পান না। আপনি অন্য লোকেদের ভয় পান

Nein, Sie haben keine Angst vor künstlicher Intelligenz. Du hast Angst vor anderen Menschen

No, no le tienes miedo a la inteligencia artificial. Tienes miedo de otras personas

Non, vous n'avez pas peur de l'intelligence artificielle. Vous avez peur des autres

नहीं, आप आर्टिफिशियल इंटेलिजेंस से नहीं डरते। आप अन्य लोगों से डरते हैं

いいえ、人工知能を恐れることはありません。他人が怖い

아니요, 당신은 인공지능을 두려워하지 않습니다. 당신은 다른 사람을 두려워합니다

Não, você não tem medo da inteligência artificial. Você tem medo de outras pessoas

Нет, вы не боитесь искусственного интеллекта. Вы боитесь других людей

Hayır, Yapay Zekadan Korkmuyorsunuz. Başkalarından Korkuyorsunuz

Không, bạn không sợ trí tuệ nhân tạo. Bạn sợ người khác

不，你并不害怕人工智能。你害怕别人

This interview series celebrates all the phenomenal . Congratulations! Well-Deserved, Champion.The HackerNoon community is excited to learn more about you! Startups of the Year Winners share the link to your winning city award here http://hackernoon.com/startups/europe/europe-bari-apulia-italy What does it mean for you to win this title? As a little team from Italy, being recognized abroad is very challenging, but it demonstrates that our team, little by little, is expanding beyond the national border and gaining more traction thanks also to this little reward that we achieved. P.S. We in 3rd position in all of Europe, so we are the 3rd best startup in Europe. Wow! arrived What sets you apart from the competition? Our business is in the blockchain and NFT field, but where the competition can create standard NFTs and collections, our team made a lot of R&D and achieved something great from physical NFTs to the first portable NFT distributor to web3 blockchain videogame, like the first blockchain NFT videogame for GameBoy. What do you love about your team, and why are you the ones to solve this problem? We have a small team, and this is the key to developing new products and elaborating fast strategies to test and implement new technology that lets our startup move fast and integrate new software and platforms to speed up some processes or to automate others in more we have a great CTO that can master several fields in the dev sector so sometimes we create or integrate some external APIs to our systems. If you weren’t building your startup, what would you be doing? It is difficult to say because our team already has great experience in different fields, and we decided to bring them together under our startup instead of working for other companies that would launch or offer products that we’ll end up developing for them in the future. At the moment, how do you measure success? What are your core metrics? We are based in South Italy, and because we are in Europe, for us, the success is to make great products and services, trying to consume less energy and waste as possible, so to be aware of the amount of our progress, we monitor daily our CO2 emissions, so we compare year after year our impact on the environment, and every year we release a report where there is all the key metric that is worth to track: Tell us how your startup is changing the world. Our focus is to give the best and most advanced tool available in the blockchain space to small and medium businesses because, especially in South Italy, they are often left behind due to a lack of knowledge of the field or due to overpriced solutions that are why we bring the same technology used by big companies, to small and medium companies, at a fair price. How do you or your company intend to embrace the responsibility of this title in 2024? In our case, the challenge that we want to face is to bring our little startup to become in the future a B Corporation, and so far, we have achieved little improvement so far, reaching a score of 35, not enough to be a B Corp, but we are more ahead of other companies, so we want to increase that number in this 2024: What goals are you looking forward to accomplishing in 2024? We want to create more games this year in the blockchain space and also try to lend to some major video game stores to reach more users. This a very challenging task because not all stores let devs bring blockchain videogame, so we are working to make our game fit in some videogame stores and let them know that the next generation of videogames are web3 videogames, where users own their items and progress, without the risk to shut down the server in the feature, because the server is on the blockchain! Which trend(s) are you most excited about in 2024? Share your reasons. Certainly, the one linked to artificial intelligence because there are every day a new tool or a new platform that automate or make easier a task that in the past where needed a person to make it possible, and in our case, we are testing and integrating some tools that are just perfect for small startups like us (have You tried Mockey?) 2023 had been another crazy year, especially in tech, with layoffs and the Generative AI takeover! Which trend are you most concerned about? Be as brief or as detailed as you like. In the future, this technology will progress without any problems and will be more accessible to more people; these people will use it in an improper way to create content, photos, and videos without the right permission to do so, especially in the deep fake field, where by now the voice cloning tool is evolving at high speed, and after that, the face cloning will be as simple as going on a bicycle. Share your biggest success so far and/or your biggest failure so far. One of the great achievements we have made so far is to create a blockchain NFT game for the iconic Gameboy from Nintendo, where not only we developed a game, but in more, we inserted an NFT so when completing the game, You receive an NFT, where You can store or sell on a public NFT marketplace, everything made possible using the EOS blockchain ( ): You can play for free on Itch We would love your feedback on HackerNoon as a tech publication! How has your experience been with us? With the team of HackerNoon, we have a special feeling because even though they started as little as us, they are now one of the best platforms to know everything in the tech field, with detailed guides in different sectors, from AI to blockchain and they even made a little documentary about crypto and blockchain. Any words of wisdom you’d like to share with us? There is incredible strength in being constant in the most difficult challenges. Like the sea that continues to crash against the rocks, never give up, because it is precisely in those moments of struggle and perseverance that the most extraordinary success stories are shaped. Startups of The Year is HackerNoon’s Flagship community-driven event celebrating startups that survived and thrived in 2023. 30,000 startups across 4200+ cities and six continents participated this year to be crowned the best startup in their city. See our global winners announcement . here Companies that blog more get 67% more leads - Jumpstart your company’s blogging journey by purchasing our . Business Blogging Package The 2023 Startups Of The Year is sponsored by: . . The winners will get a free .Tech Domain, a HackerNoon NFT, and a Tech Company News Page. TECH Domains

Meet Hoken Tech, Winner of the Startups of the Year in Bari

"Deep Learning is Rubbish"
 Karl Friston & Yann LeCun's Panel at the Davos 2024
World Economic Forum

From smartwatches and product recommendations to customer service chatbots and automated emails, we are officially in the era of assistive technology. However, the integration has been so seamless that only __ __believe they interact with AI daily, and 44% claim they do not interact with the technology at all. 27% of Americans Whether or not consumers believe they are actively using AI, the truth is that brands are leveraging their intelligence for business. In fact, AI is expected to add to the global economy by 2030. This is because artificial intelligence technologies like chatbots and large language models (LLMs) like ChatGPT promise to improve efficiency and boost creativity. In some cases, AI also supports the eradication of recurring business tasks like email composition, writing, editing, and even ideation. $15.7 trillion But these technologies aren’t just helping brands improve their workflows. are helping companies build brand loyalty by optimizing content libraries and enhancing the creative process. AI and ML Harness the power of AI with new strategies Owned asset optimization (OAO) gives brands a powerful strategy to reach audiences in an oversaturated digital marketplace. Patrick Danial, CTO and co-founder of Terakeet, has seen firsthand how OAO can create authentic consumer connections. The brand’s clients see a 70% to 90% decrease in customer acquisition costs. OAO maximizes the impact of digital assets fully owned and controlled by a brand to shape their own narratives and gain meaningful attention. Brands can also use and create their own methodologies to boost future content optimization processes. This helps to streamline and customize the content creation process and prepares brands for the future. AI to enhance owned assets Generative AI technologies, like GPT-4, are trained on a large volume of data, making it possible for them to generate a variety of content types and topics. But still, marketers must keep in mind that its data is limited and requires a human element to review, refine, and personalize AI-generated content. The combination of content resources, proprietary data, and brand-focused models gives companies the opportunity to seamlessly capitalize on prospective AI developments. Build from a strong foundation of data As AI continues to become a bigger part of our lives and work, marketers will have to reckon with the validity, ethics, and timeliness of the data fed into the systems. This means brands can’t completely rely on current third-party to understand their consumers in real-time. Danial says this requires tapping into reliable and up-to-date consumer data to build strategies that audiences care about. AI data sets For example, marketers could lean on proprietary data, pairing unique insights with AI efficiencies and human expertise. Or, they can leverage what is likely the most honest (and volunteered) consumer data that’s housed in organic search and Google trends to reveal behaviors and consumer priorities. However, all of this must be done strategically. The key to effectively leveraging AI for content optimization is to use it as a solution for efficiency needs, not a replacement for human-driven work or search data. Understand the creator economy As brands learn how to implement the benefits of AI into their workflows, they must understand its role in shaping the creator economy. In an era where consumers are continually bombarded with marketing strategies, there's an increasing thirst for content that is genuine, inventive, and credible. This shift is powering the burgeoning creator economy, ushering in a new age of creator marketing. Companies like Evolved Talent Agency are at the forefront of this industry, linking esports players and brands for lucrative deals. Brands looking to leverage the creator economy—and creators themselves—need representation that knows their industries. Take a look at the recent SAG-AFTRA strikes and debates over digital likeness. A good agency will work to ensure talent receives the proper value for their likeness and aid creators in navigating this AI-centric terrain, answering pivotal questions, and offering strategic guidance to their clients. At the same time, AI is responsible for the advent of content creation superpowers. Now, anyone with a smartphone can quickly and easily capture, edit, and produce high-quality content and share it across social media. From branded videos to quippy copy, AI provides a shortcut and evens the playing field for content creators. This combination of strong creative content demand with a new technology that empowers creative abilities will inevitably lead to a surge in content creators, making it harder to stand out. While this fuels the interests of consumers, marketers and brands have a greater responsibility when it comes to AI, specifically when it comes to the technology’s creative and legal impact on their work and partnerships with content creators. Use data to identify branding AI can use large amounts of data and intelligent insights to reveal which type of consumer is purchasing a brand’s products. Brands can use that information to personalize and tailor their advertising and marketing efforts to cater to the relevant consumer and drive sales. However, Nick Holmes, Director of the Trademark Practice for Caldwell, warns that AI doesn’t always discern between brands. This means consumers may speak into their phone or tablet and ask for a specific product, but the results might exclude certain brands. This can prevent brands from obtaining new consumers or finding their target market. But, he notes, it can also expose consumers to new brands and products that might not have the same resources and recognition as larger brands. AI can leverage this same technology to assist brands in finding and taking down counterfeit products or infringing brands that unlawfully use a registered trademark. While AI may present results quicker than humans, accuracy is a concern. As marketers and brands become accustomed to leveraging AI to connect with consumers, it is important to understand the technology’s abilities and limitations. Rather than expecting AI to solve every problem and present new solutions, brands must consider it another tool in their arsenal of content creation collection. By humanizing the data, insights, and capabilities behind AI, brands will find success in building meaningful connections with consumers based on an understanding of who they are, what they want, and what does and does not work for them. This way, between brand and consumer, built on a strong foundation of data and content creation. AI becomes a bridge

How AI Is Impacting Consumer-Brand Connections

BECAUSE INTELLIGENCE

becauseintelligence.com

11-50 employees

Since 2018

COMPANY RANKING

BECAUSE INTELLIGENCE

EVERGREEN INDEX #2387

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BECAUSE INTELLIGENCE

becauseintelligence.com

11-50 employees

Since 2018

COMPANY RANKING

BECAUSE INTELLIGENCE

EVERGREEN INDEX #2387

RELATED COMPANIESRANK

STORIES ABOUT BECAUSE INTELLIGENCE

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