The Reformation

thereformation

Five Weeks in a Balloon by Jules Verne, is part of the HackerNoon Books Series. You can jump to any chapter in this book . Chapter XXXVII here CHAPTER THIRTY-SEVENTH. The Western Route.—Joe wakes up.—His Obstinacy.—End of Joe’s Narrative.—Tagelei.—Kennedy’s Anxieties.—The Route to the North.—A Night near Aghades. During the night the wind lulled as though reposing after the boisterousness of the day, and the remained quietly at the top of the tall sycamore. The doctor and Kennedy kept watch by turns, and Joe availed himself of the chance to sleep most sturdily for twenty-four hours at a stretch. Victoria “That’s the remedy he needs,” said Dr. Ferguson. “Nature will take charge of his care.” With the dawn the wind sprang up again in quite strong, and moreover capricious gusts. It shifted abruptly from south to north, but finally the was carried away by it toward the west. Victoria The doctor, map in hand, recognized the kingdom of Damerghou, an undulating region of great fertility, in which the huts that compose the villages are constructed of long reeds interwoven with branches of the . The grain-mills were seen raised in the cultivated fields, upon small scaffoldings or platforms, to keep them out of the reach of the mice and the huge ants of that country. asclepia They soon passed the town of Zinder, recognized by its spacious place of execution, in the centre of which stands the “tree of death.” At its foot the executioner stands waiting, and whoever passes beneath its shadow is immediately hung! Upon consulting his compass, Kennedy could not refrain from saying: “Look! we are again moving northward.” “No matter; if it only takes us to Timbuctoo, we shall not complain. Never was a finer voyage accomplished under better circumstances!” “Nor in better health,” said Joe, at that instant thrusting his jolly countenance from between the curtains of the awning. “There he is! there’s our gallant friend—our preserver!” exclaimed Kennedy, cordially.—“How goes it, Joe?” “Oh! why, naturally enough, Mr. Kennedy, very naturally! I never felt better in my life! Nothing sets a man up like a little pleasure-trip with a bath in Lake Tchad to start on—eh, doctor?” “Brave fellow!” said Ferguson, pressing Joe’s hand, “what terrible anxiety you caused us!” “Humph! and you, sir? Do you think that I felt easy in my mind about you, gentlemen? You gave me a fine fright, let me tell you!” “We shall never agree in the world, Joe, if you take things in that style.” “I see that his tumble hasn’t changed him a bit,” added Kennedy. “Your devotion and self-forgetfulness were sublime, my brave lad, and they saved us, for the was falling into the lake, and, once there, nobody could have extricated her.” Victoria “But, if my devotion, as you are pleased to call my summerset, saved you, did it not save me too, for here we are, all three of us, in first-rate health? Consequently we have nothing to squabble about in the whole affair.” “Oh! we can never come to a settlement with that youth,” said the sportsman. “The best way to settle it,” replied Joe, “is to say nothing more about the matter. What’s done is done. Good or bad, we can’t take it back.” “You obstinate fellow!” said the doctor, laughing; “you can’t refuse, though, to tell us your adventures, at all events.” “Not if you think it worth while. But, in the first place, I’m going to cook this fat goose to a turn, for I see that Mr. Kennedy has not wasted his time.” “All right, Joe!” “Well, let us see then how this African game will sit on a European stomach!” The goose was soon roasted by the flame of the blow-pipe, and not long afterward was comfortably stowed away. Joe took his own good share, like a man who had eaten nothing for several days. After the tea and the punch, he acquainted his friends with his recent adventures. He spoke with some emotion, even while looking at things with his usual philosophy. The doctor could not refrain from frequently pressing his hand when he saw his worthy servant more considerate of his master’s safety than of his own, and, in relation to the sinking of the island of the Biddiomahs, he explained to him the frequency of this phenomenon upon Lake Tchad. At length Joe, continuing his recital, arrived at the point where, sinking in the swamp, he had uttered a last cry of despair. “I thought I was gone,” said he, “and as you came right into my mind, I made a hard fight for it. How, I couldn’t tell you—but I’d made up my mind that I wouldn’t go under without knowing why. Just then, I saw—two or three feet from me—what do you think? the end of a rope that had been fresh cut; so I took leave to make another jerk, and, by hook or by crook, I got to the rope. When I pulled, it didn’t give; so I pulled again and hauled away and there I was on dry ground! At the end of the rope, I found an anchor! Ah, master, I’ve a right to call that the anchor of safety, anyhow, if you have no objection. I knew it again! It was the anchor of the You had grounded there! So I followed the direction of the rope and that gave me your direction, and, after trying hard a few times more, I got out of the swamp. I had got my strength back with my spunk, and I walked on part of the night away from the lake, until I got to the edge of a very big wood. There I saw a fenced-in place, where some horses were grazing, without thinking of any harm. Now, there are times when everybody knows how to ride a horse, are there not, doctor? So I didn’t spend much time thinking about it, but jumped right on the back of one of those innocent animals and away we went galloping north as fast as our legs could carry us. I needn’t tell you about the towns that I didn’t see nor the villages that I took good care to go around. No! I crossed the ploughed fields; I leaped the hedges; I scrambled over the fences; I dug my heels into my nag; I thrashed him; I fairly lifted the poor fellow off his feet! At last I got to the end of the tilled land. Good! There was the desert. ‘That suits me!’ said I, ‘for I can see better ahead of me and farther too.’ I was hoping all the time to see the balloon tacking about and waiting for me. But not a bit of it; and so, in about three hours, I go plump, like a fool, into a camp of Arabs! Whew! what a hunt that was! You see, Mr. Kennedy, a hunter don’t know what a real hunt is until he’s been hunted himself! Still I advise him not to try it if he can keep out of it! My horse was so tired, he was ready to drop off his legs; they were close on me; I threw myself to the ground; then I jumped up again behind an Arab! I didn’t mean the fellow any harm, and I hope he has no grudge against me for choking him, but I saw you—and you know the rest. The came on at my heels, and you caught me up flying, as a circus-rider does a ring. Wasn’t I right in counting on you? Now, doctor, you see how simple all that was! Nothing more natural in the world! I’m ready to begin over again, if it would be of any service to you. And besides, master, as I said a while ago, it’s not worth mentioning.” Victoria! Victoria “My noble, gallant Joe!” said the doctor, with great feeling. “Heart of gold! we were not astray in trusting to your intelligence and skill.” “Poh! doctor, one has only just to follow things along as they happen, and he can always work his way out of a scrape! The safest plan, you see, is to take matters as they come.” While Joe was telling his experience, the balloon had rapidly passed over a long reach of country, and Kennedy soon pointed out on the horizon a collection of structures that looked like a town. The doctor glanced at his map and recognized the place as the large village of Tagelei, in the Damerghou country. “Here,” said he, “we come upon Dr. Barth’s route. It was at this place that he parted from his companions, Richardson and Overweg; the first was to follow the Zinder route, and the second that of Maradi; and you may remember that, of these three travellers, Barth was the only one who ever returned to Europe.” “Then,” said Kennedy, following out on the map the direction of the , “we are going due north.” Victoria “Due north, Dick.” “And don’t that give you a little uneasiness?” “Why should it?” “Because that line leads to Tripoli, and over the Great Desert.” “Oh, we shall not go so far as that, my friend—at least, I hope not.” “But where do you expect to halt?” “Come, Dick, don’t you feel some curiosity to see Timbuctoo?” “Timbuctoo?” “Certainly,” said Joe; “nobody nowadays can think of making the trip to Africa without going to see Timbuctoo.” “You will be only the fifth or sixth European who has ever set eyes on that mysterious city.” “Ho, then, for Timbuctoo!” “Well, then, let us try to get as far as between the seventeenth and eighteenth degrees of north latitude, and there we will seek a favorable wind to carry us westward.” “Good!” said the hunter. “But have we still far to go to the northward?” “One hundred and fifty miles at least.” “In that case,” said Kennedy, “I’ll turn in and sleep a bit.” “Sleep, sir; sleep!” urged Joe. “And you, doctor, do the same yourself: you must have need of rest, for I made you keep watch a little out of time.” The sportsman stretched himself under the awning; but Ferguson, who was not easily conquered by fatigue, remained at his post. In about three hours the was crossing with extreme rapidity an expanse of stony country, with ranges of lofty, naked mountains of granitic formation at the base. A few isolated peaks attained the height of even four thousand feet. Giraffes, antelopes, and ostriches were seen running and bounding with marvellous agility in the midst of forests of acacias, mimosas, souahs, and date-trees. After the barrenness of the desert, vegetation was now resuming its empire. This was the country of the Kailouas, who veil their faces with a bandage of cotton, like their dangerous neighbors, the Touaregs. Victoria At ten o’clock in the evening, after a splendid trip of two hundred and fifty miles, the halted over an important town. The moonlight revealed glimpses of one district half in ruins; and some pinnacles of mosques and minarets shot up here and there, glistening in the silvery rays. The doctor took a stellar observation, and discovered that he was in the latitude of Aghades. Victoria This city, once the seat of an immense trade, was already falling into ruin when Dr. Barth visited it. The , not being seen in the obscurity of night, descended about two miles above Aghades, in a field of millet. The night was calm, and began to break into dawn about three o’clock A.M.; while a light wind coaxed the balloon westward, and even a little toward the south. Victoria Dr. Ferguson hastened to avail himself of such good fortune, and rapidly ascending resumed his aërial journey amid a long wake of golden morning sunshine. 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. Jules Verne (2002). Five Weeks in a Balloon. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/3526/pg3526-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 , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

The Western Route

I think OpenAI is not being honest about the diminishing returns of scaling AI with data and compute alone. I think they are also putting a lot of the economy, the world and this entire industry in jeopardy by not talking more openly about the topic. At first, I believed what they told us, that all you need to do is add more compute power and more data, and LLMs as well as other models will simply get better. That this relationship between the models, their compute and data could grow linearly until the end of time. The leap from GPT-3 and GPT-3.5 was immense. The leap from GPT-3.5 to GPT-4 seemed like clear evidence that this presumption was correct. But then things got weird. Instead of releasing a model called GPT-5 or even GPT-4.5, they released GPT-4-turbo. GPT-4-turbo is not as intelligent as GPT-4 but it is much faster and it's cheaper. That all makes sense. But then, this trend kept going. After GPT-4-turbo, OpenAI's next release was GPT-4o. GPt-4o is more or less just as intelligent as GPT-4-turbo, but it is even faster and even cheaper. The functionality that really sold us, however, was its ability to talk and understand things via audio and its speed. However, take note, at this point in our story, GPT-4-turbo is not more intelligent than GPT-4 and GPT-4o is not more intelligent than GPT-4-turbo. And none of them are more intelligent than GPT-4. Their next and most recent release was GPT-o1. GPT-o1 can perform better than GPT-4 onsome tasks. But that's because o1 is not really a single model. GPT-o1 is actually a black box of multiple lightweight LLM models working together. Perhaps o1 is even better described as software or middleware than it is an actual model. You give it a question, it comes up with an answer, and then it repeatedly uses other models tasked with checking the answer to make sure it’s right, and it disguises all of these operations. It does all of this very, very quickly. Why not just make an LLM that's more powerful than GPT-4? Why resort to such cloak-and-dagger techniques to achieve new releases? GPT-4 came out 2 years ago, we should be well beyond its capabilities by now. Well, Noam Brown, a researcher at OpenAI had something to say on why they went this route with o1 at TED AI. He said “It turned out that having a bot think for just 20 seconds in a hand of poker got the same boosting performance as scaling up the model by 100,000x and training it for 100,000 times longer,” Now stop and really think about what is being said there. A bot thinking for 20 seconds is as good as a bot trained 100,000 times longer with 100,000 times more computing power.  If the scaling laws are infinite, that math is impossible. Something is either wrong here or someone is lying. Why does all of this matter? OpenAI is worth 150 billion dollars and the majority of that market cap is based on projections that depend on the improvement of models over time. If AI is only as good as it is today, that’s still an interesting future, but that’s not what’s being sold to investors by AI companies whose entire IP is their model. That also changes the product roadmap of many other companies that depend on the continued advancement of their LLMs to build their own products. OpenAI’s goal and ambitions of AGI are severely delayed if this is all true. A Hypothesis The reason LLMs are so amazing is because of a higher level philosophical phenomenon that we never considered, that language inherently possesses an extremely large amount of context and data about the world within even small sections of text. Unlike pixels in a picture or video, words in a sentence implicitly describe one another. A completely cohesive sentence is by definition, “rational”. Whether or not it’s true is a very different story and a problem that transcends language alone. No matter how much text you consume, “truth” and “falsehoods” are not simply linguistic concepts. You can say something is completely rational but in no way “true”. It is at this point LLMs will consistently hit a brick wall. Over the last 12 months, I’d like to formally speculate that behind closed doors there have been no huge leaps in LLMs at OpenAI, GrokAI, or at Google. To be specific I don’t think anyone, anywhere has made any LLM that is even 1.5X better than GPT-4. At OpenAI it seems that high-level staff are quitting. Right now they’re saying it’s because of safety but I’m going to put my tinfoil hat on now and throw an idea out there. They are aware of this issue and they’re jumping ship before it’s too late. Confirmation I started discussing this concern with friends 3 months ago. I was called many names haha. But in the last 3 weeks, a lot of the press has begun to smell something fishy: OpenAI is no longer releasing Orion (GPT-5) because it did not meet expected performance benchmarks and it is seeing diminishing returns. (https://www.theinformation.com/articles/openai-shifts-strategy-as-rate-of-gpt-ai-improvements-slows)


Bloomberg reports that OpenAI, Google and Anthropic are all having struggles making more advanced AI. (https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai) What can we do about it? It’s hard to recommend a single solution. The tech behind o1 is proof that even low-performance models can be repurposed to do complicated operations. But that is not a solution to the problem of AI scaling. I think there needs to be substantial investment and rapid testing of new model architectures. We also have run out of data and need new ways of extrapolating usable data for LLMs to be trained on. Perhaps using multidimensional labeling that helps guide its references for truthful information directly. Another good idea could be to simply continue fine-tuning LLMs for specific use cases like math, science, and healthcare running and using AI agent workflows, similar to o1. It might give a lot of companies wiggle room until a new architecture arises. This problem is really bad but I think that the creativity in machine learning and software development it will inspire will be immense. Once we get over this hurdle, we’ll certainly be well on schedule for AGI and perhaps ASI. I think OpenAI is not being honest about the diminishing returns of scaling AI with data and compute alone. I think they are also putting a lot of the economy, the world and this entire industry in jeopardy by not talking more openly about the topic. At first, I believed what they told us, that all you need to do is add more compute power and more data, and LLMs as well as other models will simply get better. That this relationship between the models, their compute and data could grow linearly until the end of time. The leap from GPT-3 and GPT-3.5 was immense. The leap from GPT-3.5 to GPT-4 seemed like clear evidence that this presumption was correct. But then things got weird. Instead of releasing a model called GPT-5 or even GPT-4.5, they released GPT-4-turbo. GPT-4-turbo is not as intelligent as GPT-4 but it is much faster and it's cheaper. That all makes sense. But then, this trend kept going. After GPT-4-turbo, OpenAI's next release was GPT-4o. GPt-4o is more or less just as intelligent as GPT-4-turbo, but it is even faster and even cheaper. The functionality that really sold us, however, was its ability to talk and understand things via audio and its speed. However, take note, at this point in our story, GPT-4-turbo is not more intelligent than GPT-4 and GPT-4o is not more intelligent than GPT-4-turbo. And none of them are more intelligent than GPT-4. Their next and most recent release was GPT-o1. GPT-o1 can perform better than GPT-4 on some tasks. But that's because o1 is not really a single model. GPT-o1 is actually a black box of multiple lightweight LLM models working together. Perhaps o1 is even better described as software or middleware than it is an actual model. You give it a question, it comes up with an answer, and then it repeatedly uses other models tasked with checking the answer to make sure it’s right, and it disguises all of these operations. It does all of this very, very quickly. some Why not just make an LLM that's more powerful than GPT-4? Why resort to such cloak-and-dagger techniques to achieve new releases? GPT-4 came out 2 years ago, we should be well beyond its capabilities by now. Well, Noam Brown, a researcher at OpenAI had something to say on why they went this route with o1 at TED AI. He said “It turned out that having a bot think for just 20 seconds in a hand of poker got the same boosting performance as scaling up the model by 100,000x and training it for 100,000 times longer,” Now stop and really think about what is being said there. A bot thinking for 20 seconds is as good as a bot trained 100,000 times longer with 100,000 times more computing power.  If the scaling laws are infinite, that math is impossible. Something is either wrong here or someone is lying. Why does all of this matter? OpenAI is worth 150 billion dollars and the majority of that market cap is based on projections that depend on the improvement of models over time. If AI is only as good as it is today, that’s still an interesting future, but that’s not what’s being sold to investors by AI companies whose entire IP is their model. That also changes the product roadmap of many other companies that depend on the continued advancement of their LLMs to build their own products. OpenAI’s goal and ambitions of AGI are severely delayed if this is all true. A Hypothesis The reason LLMs are so amazing is because of a higher level philosophical phenomenon that we never considered, that language inherently possesses an extremely large amount of context and data about the world within even small sections of text. Unlike pixels in a picture or video, words in a sentence implicitly describe one another. A completely cohesive sentence is by definition, “rational”. Whether or not it’s true is a very different story and a problem that transcends language alone. No matter how much text you consume, “truth” and “falsehoods” are not simply linguistic concepts. You can say something is completely rational but in no way “true”. It is at this point LLMs will consistently hit a brick wall. Over the last 12 months, I’d like to formally speculate that behind closed doors there have been no huge leaps in LLMs at OpenAI, GrokAI, or at Google. To be specific I don’t think anyone, anywhere has made any LLM that is even 1.5X better than GPT-4. At OpenAI it seems that high-level staff are quitting. Right now they’re saying it’s because of safety but I’m going to put my tinfoil hat on now and throw an idea out there. They are aware of this issue and they’re jumping ship before it’s too late. Confirmation Confirmation I started discussing this concern with friends 3 months ago. I was called many names haha. But in the last 3 weeks, a lot of the press has begun to smell something fishy: OpenAI is no longer releasing Orion (GPT-5) because it did not meet expected performance benchmarks and it is seeing diminishing returns. (https://www.theinformation.com/articles/openai-shifts-strategy-as-rate-of-gpt-ai-improvements-slows) Bloomberg reports that OpenAI, Google and Anthropic are all having struggles making more advanced AI. (https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai) OpenAI is no longer releasing Orion (GPT-5) because it did not meet expected performance benchmarks and it is seeing diminishing returns. (https://www.theinformation.com/articles/openai-shifts-strategy-as-rate-of-gpt-ai-improvements-slows) OpenAI is no longer releasing Orion (GPT-5) because it did not meet expected performance benchmarks and it is seeing diminishing returns. ( https://www.theinformation.com/articles/openai-shifts-strategy-as-rate-of-gpt-ai-improvements-slows ) OpenAI is no longer releasing Orion (GPT-5) because it did not meet expected performance benchmarks and it is seeing diminishing returns. https://www.theinformation.com/articles/openai-shifts-strategy-as-rate-of-gpt-ai-improvements-slows Bloomberg reports that OpenAI, Google and Anthropic are all having struggles making more advanced AI. (https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai) Bloomberg reports that OpenAI, Google and Anthropic are all having struggles making more advanced AI. ( https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai ) Bloomberg reports that OpenAI, Google and Anthropic are all having struggles making more advanced AI. https://www.bloomberg.com/news/articles/2024-11-13/openai-google-and-anthropic-are-struggling-to-build-more-advanced-ai What can we do about it? It’s hard to recommend a single solution. The tech behind o1 is proof that even low-performance models can be repurposed to do complicated operations. But that is not a solution to the problem of AI scaling. I think there needs to be substantial investment and rapid testing of new model architectures. We also have run out of data and need new ways of extrapolating usable data for LLMs to be trained on. Perhaps using multidimensional labeling that helps guide its references for truthful information directly. Another good idea could be to simply continue fine-tuning LLMs for specific use cases like math, science, and healthcare running and using AI agent workflows, similar to o1. It might give a lot of companies wiggle room until a new architecture arises. This problem is really bad but I think that the creativity in machine learning and software development it will inspire will be immense. Once we get over this hurdle, we’ll certainly be well on schedule for AGI and perhaps ASI. software development

Is AI Progress Slowing? The Scaling Debate OpenAI Doesn’t Want to Have

¿Se está ralentizando el progreso de la IA? El debate sobre la escalabilidad que OpenAI no quiere tener

האם התקדמות הבינה המלאכותית מואטת? הדיון בקנה מידה ש-OpenAI לא רוצה שיהיה

Apakah Kemajuan AI Melambat? Perdebatan Skala yang Tidak Diinginkan OpenAI

Il progresso dell'intelligenza artificiale sta rallentando? Il dibattito sulla scalabilità che OpenAI non vuole avere

AIの進歩は鈍化しているのか？OpenAIが望まないスケーリングの議論

Bokóli ya AI ezali kokita? Débat ya Échelle OpenAI Elingi Ezala Te

Vertraagt de vooruitgang van AI? Het schaaldebat dat OpenAI niet wil hebben

Spomaľuje sa pokrok AI? Debata o škálovaní OpenAI nechce mať

Saktar AI-utvecklingen ner? Skalningsdebatten som OpenAI inte vill ha

AI ösüşi haýalmy? Giňeldilen jedel OpenAI islemeýär

Чи сповільнюється розвиток ШІ? Дебати щодо масштабування, яких OpenAI не хоче мати

Ingabe Intuthuko ye-AI Iyahamba Kancane? I-Scaling Debate OpenAI Ayifuni Ukuba Nayo

The contemporary discourse on generative Artificial Intelligence (AI) presents a nuanced and dualistic narrative of technological development. I will delve into contrasting perspectives surrounding the current state and future of generative AI, juxtaposing the pervasive sentiments of disillusionment against the sustained advancements in the field. Notably, despite apparent stagnation in some sectors and declining public interest, significant strides in AI technology and applications continue to emerge. This analysis provides a nuanced examination of the cycle of hype, stabilization, and potential revolutionary impact of generative AI, comparing it with historical technological disruptions such as the printing press, electricity, and the internet. Through a balanced review of both setbacks and breakthroughs in the AI landscape, I aim to discern whether generative AI is merely experiencing a temporary lull or if it signifies a broader technological revolution. By critically assessing the evidence and forecasting future trends, the article also explores the implications of this technology on societal norms and industry practices, ultimately questioning the revolutionary potential of generative AI amidst ongoing challenges and evolving expectations. Economic Performance and Market Valuations Recent data suggest that the economic outcomes related to generative AI have not aligned with prior expectations. For instance, despite significant investments in hardware, such as the $50 billion spent on Nvidia equipment, the return, in terms of revenue, has been relatively modest, amounting to only $3 billion (The Wall Street Journal). Additionally, there is a notable stagnation in visits to AI-focused websites (Exponential View), and venture capital firm Sequoia has highlighted the overvaluation of AI startups, suggesting a disconnect between market valuations and underlying economic realities (The Information). Industry Challenges and Strategic Adjustments Several high-profile AI startups have experienced difficulties, signaling potential instability within the sector. For example, InflectionAI has been effectively disbanded, with Microsoft acquiring its assets, including the expertise of former CEO Mustafa Suleyman (TechCrunch). Moreover, StabilityAI faces uncertain prospects following leadership controversies (Forbes). Additionally, the broader enterprise adoption of AI technologies is hampered by concerns over security and ethical implications (Diginomica). Public Perception and Technological Engagement While the initial public enthusiasm for AI technologies like ChatGPT has waned, a subset of users, particularly software developers, continue to find value in these tools (Pew Research Center). This contrasts with the broader perception that AI tools serve more as novelties rather than practical aids in productivity (The Register). Innovative Developments and Future Prospects Despite these challenges, the development of AI technologies continues at a rapid pace. New models like Claude 3 from Anthropic are setting benchmarks in AI capabilities (Anthropic). The field also anticipates the arrival of advanced models such as OpenAI's GPT-5, signaling ongoing innovation and potential market recovery (Business Insider). Historical Perspective on Generative AI Development Tyler Cowen, in his analysis, proposes that the current state of AI reflects a natural progression seen in other revolutionary technologies. Drawing parallels to the adoption of the printing press, electricity, and the internet, Cowen suggests that the lifecycle of transformative technologies typically transitions through phases of hype, stabilization, and eventual widespread utility. This pattern, he argues, is evident in the current trajectory of generative AI technologies (Bloomberg). Cowen articulates that while the initial excitement surrounding generative AI has diminished—a phase characterized by inflated expectations and speculative investments—the underlying advancements in technology continue to progress significantly. This 'silent lull' is not a regression but a recalibration of expectations as the technology matures and integrates more deeply into various sectors. Generative AI, despite facing skepticism regarding its immediate impacts, mirrors the developmental paths of its historical counterparts. Notably, the internet, post-dot-com bubble, and the gradual integration of electricity into industrial processes both experienced periods of underwhelming performance followed by significant, long-term contributions to economic and social structures. Recent developments in AI technology further support Cowen's thesis. OpenAI's enhancement of enterprise services and the advancement of models like Google's GPT-4 competitor illustrate ongoing innovation within the field (ZDNet, Google). Moreover, the rapid progression of open-source AI models, although less visible to the casual user, underscores a robust, underlying growth in AI capabilities that continues to push the boundaries of what these technologies can achieve (Archive). The Path Forward Despite the optimism expressed by some industry leaders, there are notable challenges and setbacks that temper the enthusiastic projections about AI. Issues such as the slower-than-anticipated adoption rates in enterprises and the mixed results of new AI products like Google Gemini Advanced highlight the complex reality facing AI development (Diginomica, The Algorithmic Bridge). The question remains whether generative AI will indeed follow the transformative paths of its predecessors or diverge due to unique challenges and societal dynamics. The industry's ability to navigate these challenges, coupled with ongoing technical advancements, will likely determine the trajectory of AI's impact on society. Concluding Thoughts Generative AI's journey is marked by cycles of hype and recalibration, similar to earlier technologies. While immediate outcomes may seem underwhelming, the continued development and integration of AI into various sectors may very well underpin the next wave of significant technological and societal transformations. As with historical innovations, the true measure of AI's impact will likely be observed in hindsight, shaped by a complex interplay of technological capabilities, market forces, societal acceptance, and regulatory environments. References "A Peter Thiel-backed AI startup seeks $2 billion valuation" - The Wall Street Journal. Available at: https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d
"Growth and investment in AI technology" - Exponential View. Available at: https://substack.com/@exponentialview/note/c-52677620
"AI startups overvalued" - The Information. Available at: https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal
"Inflection AI dismantled" - TechCrunch. Available at: https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/
"Stability AI's uncertain future" - Forbes. Available at: https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/
Tyler Cowen on AI's ongoing revolution despite subdued hype - Bloomberg
OpenAI introduces business version of ChatGPT - ZDNet
Challenges in AI adoption within enterprises - Diginomica
Google's GPT-4 and its marketplace challenges - The Algorithmic Bridge The contemporary discourse on generative Artificial Intelligence (AI) presents a nuanced and dualistic narrative of technological development. I will delve into contrasting perspectives surrounding the current state and future of generative AI, juxtaposing the pervasive sentiments of disillusionment against the sustained advancements in the field. Notably, despite apparent stagnation in some sectors and declining public interest, significant strides in AI technology and applications continue to emerge. This analysis provides a nuanced examination of the cycle of hype, stabilization, and potential revolutionary impact of generative AI, comparing it with historical technological disruptions such as the printing press, electricity, and the internet. Through a balanced review of both setbacks and breakthroughs in the AI landscape, I aim to discern whether generative AI is merely experiencing a temporary lull or if it signifies a broader technological revolution. By critically assessing the evidence and forecasting future trends, the article also explores the implications of this technology on societal norms and industry practices, ultimately questioning the revolutionary potential of generative AI amidst ongoing challenges and evolving expectations. Economic Performance and Market Valuations Economic Performance and Market Valuations Recent data suggest that the economic outcomes related to generative AI have not aligned with prior expectations. For instance, despite significant investments in hardware, such as the $50 billion spent on Nvidia equipment, the return, in terms of revenue, has been relatively modest, amounting to only $3 billion ( The Wall Street Journal ). Additionally, there is a notable stagnation in visits to AI-focused websites ( Exponential View ), and venture capital firm Sequoia has highlighted the overvaluation of AI startups, suggesting a disconnect between market valuations and underlying economic realities ( The Information ). The Wall Street Journal Exponential View The Information Industry Challenges and Strategic Adjustments Industry Challenges and Strategic Adjustments Several high-profile AI startups have experienced difficulties, signaling potential instability within the sector. For example, InflectionAI has been effectively disbanded, with Microsoft acquiring its assets, including the expertise of former CEO Mustafa Suleyman ( TechCrunch ). Moreover, StabilityAI faces uncertain prospects following leadership controversies ( Forbes ). Additionally, the broader enterprise adoption of AI technologies is hampered by concerns over security and ethical implications ( Diginomica ). TechCrunch Forbes Diginomica Public Perception and Technological Engagement Public Perception and Technological Engagement While the initial public enthusiasm for AI technologies like ChatGPT has waned, a subset of users, particularly software developers, continue to find value in these tools ( Pew Research Center ). This contrasts with the broader perception that AI tools serve more as novelties rather than practical aids in productivity ( The Register ). Pew Research Center The Register Innovative Developments and Future Prospects Innovative Developments and Future Prospects Despite these challenges, the development of AI technologies continues at a rapid pace. New models like Claude 3 from Anthropic are setting benchmarks in AI capabilities ( Anthropic ). The field also anticipates the arrival of advanced models such as OpenAI's GPT-5, signaling ongoing innovation and potential market recovery ( Business Insider ). Anthropic Business Insider Historical Perspective on Generative AI Development Tyler Cowen, in his analysis, proposes that the current state of AI reflects a natural progression seen in other revolutionary technologies. Drawing parallels to the adoption of the printing press, electricity, and the internet, Cowen suggests that the lifecycle of transformative technologies typically transitions through phases of hype, stabilization, and eventual widespread utility. This pattern, he argues, is evident in the current trajectory of generative AI technologies ( Bloomberg ). Bloomberg Cowen articulates that while the initial excitement surrounding generative AI has diminished—a phase characterized by inflated expectations and speculative investments—the underlying advancements in technology continue to progress significantly. This 'silent lull' is not a regression but a recalibration of expectations as the technology matures and integrates more deeply into various sectors. Generative AI, despite facing skepticism regarding its immediate impacts, mirrors the developmental paths of its historical counterparts. Notably, the internet, post-dot-com bubble, and the gradual integration of electricity into industrial processes both experienced periods of underwhelming performance followed by significant, long-term contributions to economic and social structures. Recent developments in AI technology further support Cowen's thesis. OpenAI's enhancement of enterprise services and the advancement of models like Google's GPT-4 competitor illustrate ongoing innovation within the field ( ZDNet , Google ). Moreover, the rapid progression of open-source AI models, although less visible to the casual user, underscores a robust, underlying growth in AI capabilities that continues to push the boundaries of what these technologies can achieve ( Archive ). ZDNet Google Archive The Path Forward The Path Forward Despite the optimism expressed by some industry leaders, there are notable challenges and setbacks that temper the enthusiastic projections about AI. Issues such as the slower-than-anticipated adoption rates in enterprises and the mixed results of new AI products like Google Gemini Advanced highlight the complex reality facing AI development ( Diginomica , The Algorithmic Bridge ). Diginomica The Algorithmic Bridge The question remains whether generative AI will indeed follow the transformative paths of its predecessors or diverge due to unique challenges and societal dynamics. The industry's ability to navigate these challenges, coupled with ongoing technical advancements, will likely determine the trajectory of AI's impact on society. Concluding Thoughts Concluding Thoughts Generative AI's journey is marked by cycles of hype and recalibration, similar to earlier technologies. While immediate outcomes may seem underwhelming, the continued development and integration of AI into various sectors may very well underpin the next wave of significant technological and societal transformations. As with historical innovations, the true measure of AI's impact will likely be observed in hindsight, shaped by a complex interplay of technological capabilities, market forces, societal acceptance, and regulatory environments. References "A Peter Thiel-backed AI startup seeks $2 billion valuation" - The Wall Street Journal. Available at: https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d "Growth and investment in AI technology" - Exponential View. Available at: https://substack.com/@exponentialview/note/c-52677620 "AI startups overvalued" - The Information. Available at: https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal "Inflection AI dismantled" - TechCrunch. Available at: https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/ "Stability AI's uncertain future" - Forbes. Available at: https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/ Tyler Cowen on AI's ongoing revolution despite subdued hype - Bloomberg OpenAI introduces business version of ChatGPT - ZDNet Challenges in AI adoption within enterprises - Diginomica Google's GPT-4 and its marketplace challenges - The Algorithmic Bridge "A Peter Thiel-backed AI startup seeks $2 billion valuation" - The Wall Street Journal. Available at: https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d "Growth and investment in AI technology" - Exponential View. Available at: https://substack.com/@exponentialview/note/c-52677620 https://substack.com/@exponentialview/note/c-52677620 "AI startups overvalued" - The Information. Available at: https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal https://www.theinformation.com/articles/ai-agenda-openai-is-a-relative-steal "Inflection AI dismantled" - TechCrunch. Available at: https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/ https://techcrunch.com/2023/06/29/inflection-ai-lands-1-3b-investment-to-build-more-personal-ai/ "Stability AI's uncertain future" - Forbes. Available at: https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/ https://www.forbes.com/sites/kenrickcai/2024/03/29/how-stability-ais-founder-tanked-his-billion-dollar-startup/ Tyler Cowen on AI's ongoing revolution despite subdued hype - Bloomberg Bloomberg OpenAI introduces business version of ChatGPT - ZDNet ZDNet Challenges in AI adoption within enterprises - Diginomica Diginomica Google's GPT-4 and its marketplace challenges - The Algorithmic Bridge The Algorithmic Bridge

Generative AI in 2024: Navigating the Evolution from Hype to Transformation

2024 সালে জেনারেটিভ এআই: হাইপ থেকে রূপান্তরে বিবর্তন নেভিগেট করা

Generative KI im Jahr 2024: Vom Hype zur Transformation

IA generativa en 2024: navegando por la evolución del entusiasmo a la transformación

L'IA générative en 2024 : naviguer dans l'évolution du battage médiatique à la transformation

2024 में जनरेटिव एआई: प्रचार से परिवर्तन तक विकास की यात्रा

2024 年の生成 AI: 誇大宣伝から変革への進化をナビゲート

2024년의 생성적 AI: 과대 광고에서 혁신으로의 진화 탐색

IA generativa em 2024: navegando na evolução do hype à transformação

Генеративный ИИ в 2024 году: путь эволюции от хайпа к трансформации

2024'te Üretken Yapay Zeka: Heyecandan Dönüşüme Evrimi Yönlendirmek

AI sáng tạo vào năm 2024: Điều hướng quá trình phát triển từ cường điệu đến chuyển đổi

2024 年的生成式人工智能：从炒作到转型

The Missing Blockchain User Guide

Ten years ago, almost to the day, my husband Sam took a video of me curled up in bed, convinced I had food poisoning. I was so nauseous, I felt like I couldn’t move. It turned out it was just nerves. I had just told my parents I was going to leave a plum reporting job at The Wall Street Journal to start something new. It was the moment my decision to become a startup founder and to launch The Information became really real. Sam showed me the picture a week ago (finally something useful came out of his record-everything habit!), and it got me thinking: What would I tell that young woman curled up in bed about what lay in store for her? How would I advise that less experienced version of me—and any other startup founder or business leader who feels paralyzed by a big professional risk? As I look back on ten years of The Information, I am tremendously proud of our journalism and the fact that we’ve built one of the largest (profitable!) subscription businesses in news. I plan to carve out time over the coming months to reread many of the stories we’ve broken and reassess the industry changes that followed. I think it is also a good moment to step back and think about where the industry is headed in the next 10 years. Expect bold predictions. But first, I wanted to measure out some of my own lessons over the past 10 exciting, eventful and, yes, nerve-rattling years. So I wrote out 11 pieces of advice to that younger me: The hard things will be way easier than you think. The easy ones will be way harder. You knew the journalism would be tough. And it is. Uncovering facts that powerful people are trying to hide requires relentlessness, intelligence and grit. But that will be nothing compared to the emotional toll of leadership. Again and again, you will make a choice (a hiring, a firing, a business gamble) that is unpopular. You will feel lonely and attacked and exhausted by trying to explain yourself. Over time, leading through those moments will get easier, but it won’t come as naturally to you as reporting does. Recognize your strengths and weaknesses as early as you can and be willing to learn from them. If you want things to change, change them. Some time in the future, you will be trying to fix your morning editors meeting, where the team takes stock of the news we are reporting that day. It has gotten long and tedious and not very fun. You will stress about it for a few weeks before realizing you can just change it up. Now it’s your favorite meeting of the week. If something is not working, change it early and often. It’s not just you: No one knows what they are doing. You took a different path on your business model from the start. And people thought you were crazy. You weren’t. But every month, you will be confronted by someone with a very wise theory about what you should do. You will look out at the world and see so many people who seem so confident and have all sorts of advice. Listen to their advice but don’t assume they are right. Make the best decision you can and fix it if you screw up. Keep moving. Communicate. As a journalist, you’re used to synthesizing complex ideas and communicating them to readers. But it will take you years to recognize that you are not nearly as good at communicating with your team. You don’t prioritize it enough because you underestimate the degree to which the team finds it useful. Communicate consistently and your team will appreciate it more than you realize. It is all about you…and never about you. You will soon learn that the team will react to every word you say and mood you express—even what you eat for lunch. You will hate this but learn to accept it. You will soon have a very challenging time with a co-worker and won’t be able to figure out what you are doing wrong. You will soon learn that his cat died. Don’t read too much into things that have nothing to do with you. Take time for people you care about. Entrepreneurship is absorbing. You will have three kids you adore, and they will grow up too fast. Supporting your family and your team is all-consuming, and you will occasionally forget about all the other people close to you who believe in you—inside and outside the company. Lean on them when you need to and keep them in the loop, even if you don’t have as much time for them as you wish. Keep going. Your biggest strength will be your perseverance. Nothing comes easy, and you shouldn’t expect it to. But if you have enough energy to keep on going, you will get to the next level and then the next level—as long as you stay in the game. And if something is wrong (your sleep, an injury), fix it—or go surfing. And then fix it. Take the feedback. You are still working on this part. You appreciate the feedback you receive and you act on some of it. But you receive a lot of advice that aggravates you—generally the stuff you feel you have worked hard on and still haven’t fixed. Realize that honest feedback is a gift, and that when you are the boss, you can never get enough of it. So take it and keep the ones who give it close. But think carefully about whose opinions you care about. You will spend too long worrying about what outsiders think about you—the media reporter who won’t write about The Information, the banker who won’t invite you to his conference. Get over it and focus on your customers and team. Only they determine your destiny. Don’t stop reporting. There are days when you won’t feel very good at this job. Make sure to tap into your confidence source, which is also your joy. It’s the reporting. Call a source or two and break some news. Take the byline and smile. Pause and give yourself some credit. You will feel as you did in bed with the “food poisoning” again and again—but each episode will be shorter and more forgettable. Learn to be grateful for those nerve-testing moments and for the growth that comes out of them. And younger Jessica—good job. This article was written by Jessica Lessin, founder and editor-in-chief of . We are a global publication committed to original reporting and in-depth analysis of the technology industry. For full access to our journalism, and save up to $250 on your first year. The Information subscribe today Also appears . here

The 11 Pieces of Advice I Would Give to My Younger Self — Thoughts on Building 'The Information'

11 টি উপদেশ আমি আমার অল্পবয়সী ব্যক্তিকে দেব - 'তথ্য' তৈরির বিষয়ে চিন্তাভাবনা

Die 11 Ratschläge, die ich meinem jüngeren Ich geben würde – Gedanken zum Aufbau von „Informationen“

Los 11 consejos que le daría a mi yo más joven: reflexiones sobre cómo desarrollar 'la información'

Les 11 conseils que je donnerais à mon jeune moi — Réflexions sur la création de « l'information »

सलाह के 11 टुकड़े जो मैं अपने युवा स्व को दूंगा - 'सूचना' के निर्माण पर विचार

若い頃の自分に贈る 11 のアドバイス — 「情報」の構築についての考え

젊은 나에게 주고 싶은 11가지 조언 - '정보' 구축에 대한 생각

Os 11 conselhos que eu daria ao meu eu mais jovem - reflexões sobre como construir 'a informação'

Gençliğime Vereceğim 11 Tavsiye — 'Bilgiyi' Oluşturmak Üzerine Düşünceler

11 lời khuyên tôi sẽ đưa ra cho bản thân khi còn trẻ — Suy nghĩ về việc xây dựng 'Thông tin'

我给年轻时的自己的 11 条建议——关于构建“信息”的思考

Stories, News & Mentions about THEREFORMATION

Thereformation’s Stories on HackerNoon