{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-07-18T16:54:23.898379Z","iopub.execute_input":"2023-07-18T16:54:23.898758Z","iopub.status.idle":"2023-07-18T16:54:23.944079Z","shell.execute_reply.started":"2023-07-18T16:54:23.898730Z","shell.execute_reply":"2023-07-18T16:54:23.942738Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# **Generative AI as a leading domain in AI development.**\n\n***\n\n(This description is the first try, so the next day it will be more worked out)","metadata":{}},{"cell_type":"markdown","source":"## **Introduction**\n\nThe present year has demonstrated that Artificial Intelligence, a concept long predicted and championed by enthusiasts, while simultaneously disclaimed and rejected by many others, has garnered significant attention and showcased impressive implementations in applications such as Chat GPT and DALL-E by OpenAI and MidJourney. The increasing public interest and economic influence have necessitated a comprehensive analysis of this groundbreaking phenomenon, delving into its intricacies and contemplating its potential impact and consequences in great detail. This paper aims to analyze the basis of Generative AI, its current understanding and forthcoming implementations. \nGenerative AI term clarification","metadata":{}},{"cell_type":"markdown","source":"## **Generative AI term clarification**\nIntuitively understandable and widely used the term AI nevertheless needs some clarification before being more precisely considered as a phenomenon attracting a huge amount of attention in recent year. According to Stanford Encyclopedia of Philosophy (Artificial Intelligence, 2018) “The field of artificial intelligence (AI) officially started in 1956, launched by a small but now-famous DARPA-sponsored summer conference at Dartmouth College, in Hanover, New Hampshire” which was participated by a group of now extremely famous founders of modern computer science: John McCarthy, Claude Shannon, Marvin Minsky, Arthur Samuel, Trenchard Moore, Ray Solomonoff, Oliver Selfridge, Allen Newell, and Herbert Simon. “The term ‘artificial intelligence’ was coined there”. Six years earlier, level of AI demanded at that time as a general goal was expressed in a famous landmark presented by Alan Turing in Mind paper of 1950 and expressed in the question: “Can a machine be linguistically indistinguishable from a human?” In the following consideration Stanford Encyclopedia of Philosophy mentions classification presented by Stuart Russell and Peter Norvig who proposed systems that may be considered as Artificial Intelligence being agents placed in a two dimensional basis of acting like humans and acting rationally:\n\n\n\n| | Reasoning-Based | Behavior-Based |\n|:---------------------:|---------------------------------|-------------------------------|\n| **Human-Base** |Systems that think like humans |Systems that act like humans |\n| **Ideal Rationality** | Systems that think rationally |Systems that act rationally |\n\n\n
Four Possible Goals for AI According to AIMA
\n\n\nHaving this basis, we now able to classify available and popular AI agents and exclude those that do not fall in the definition provided. \nThe authors of this basis, Stuart Russell and Peter Norvig favored “acting rationally” as the main criteria for determining intelligent agents to be accepted as Artificial Intelligence (Russell, 2009). \n\nIn addition, according to Wikipedia article (Artificial intelligence, 2023), the **traditional goals** of AI research include:\n1. reasoning\n2. knowledge representation\n3. planning\n4. learning\n5. natural language processing\n6. perception\n7. the ability to move and manipulate objects\n8. the ability to solve an arbitrary problem\n9. mathematical optimization\n10. formal logic\n11. artificial neural networks\n12. methods based on statistics and probability\n\nNow consider what aspects are in a core of Generative AI which is a branch of AI in general. According McKinzy & Company (McKinsey&Company, J2023), Generative artificial intelligence (AI) is presented by algorithms that can be used to create new content, including audio, code, images, text, simulations, and videos. So the essential aspect that discriminates the sub brunch of Generative AI from other AI domains is an ability to create a new content and by this way to produce additional values, comparing to analyzing and classifying subsets of AI. On the other hand, the latest implementations of Generative AI, such as Chat GPT, which combine analyzing and generative abilities (or in classification Russell&Norvig acting rationally and simultaneously acting like humans) providing impressive outcomes. \nThe same point of view on the essence of Generative AI is provided by Gartner, (Top Generative AI Questions for Your Enterprise, 2023), the two main parts represent analytical part creating generalized model of the set of cases, invents, objects and generative part which creates new representatives of the set on the base of generalized model. \n(It is worth noticing that there was a great number of analytical algorithms since the beginning of computer era, as well as generative algorithms. However, it is only in recent times that the combination of the analytical and generative aspects, reinforced by multiple feedback loops and coupled with the advancements in CPU and memory productivity, has led to such tremendous results. According to McKinsey report this system classifyed as Foundation models (a very big deep learning system) coupled with generative abilities ) \nHaving this descriptive definition as a landmark and taking in account the Kaggle’s task overview where the tasks were defined as follows: \n 1) provide an expertise to centralize and summarize the rapid advancements in AI from the past two years \n 2) to describe what the community has learned over the past 2 years of working and experimenting\nwe can now solidify the aim of this essay and define its main directions. \nAdditionally, to concentrating on analytics devoted to Generative AI it is necessary to mention the other aspects such as possible ethical, sociological and economical impacts, without which the consideration would have been incomplete.","metadata":{}},{"cell_type":"markdown","source":"## **Current implementations of Generative AI**\n\nHowever, while the main implementations of Generative AI may be well-known to the technically advanced public, it is worth reiterating them here, combined with a field of implementation, to underscore their extensive impact on modern society. Furthermore, it is essential to highlight the growing range of industries that have been influenced and transformed by Generative AI. This are branches and products where Generative AI is mostly presented:\n\n**Content creation:** Generative AI can be used to create new content \n**text:** GPT-3, LaMDA, LLaMA, BLOOM, GPT-4 \n**images:** Imagen, DALL-E, Midjourney, Adobe Firefly, Stable Diffusion \n**code:** OpenAI Codex, GPT-3 and GitHub Copilot, Duet AI for Google Cloud \n**movies:** Gen1 and Gen2 by RunwayML, Make-A-Video by Meta Platforms \n**music:** MusicLM \n**computer games:** No Man’s Sky, Minecraft, AI Dungeon \n\n\nWe can see what Kaggle community has learned over the past 2 years of working and experimenting (with AI) looking on the data provided. \nThe Kaggle community is presented by extremely wide variety of researchers, and professionals having their individual background and style of working and their projects are expected to be not limited by Kagle platform. Some clues could be figured out from materials provided by Kaggle itself particularly for this essay. First let’s analyze the arXiv_metadata.json file. It is necessary to remember that for the year 2023 the data presented only for the beginning of the year. \n\nFirst let us look the number of : \nterm ‘AI’ use over the years of publication \ncommon use of terms ‘AI’ and ‘generative’ in one publication \nUse of term ‘generative AI’ as a complete phrase \n\n![picturte_2.jpg](attachment:13fb91a0-5880-4698-a704-56ccabfad499.jpg)\n\nIt is seen from the chart that:\n1)\tThe number of publications on AI in general has an explosive growth since 2017\n2)\tPublications mentioning AI as a generative process began arriving only at 2014\n3)\tFully coined term generative AI is used only science 2020\nThe next char represents the annual growth of publications for those three categories.\n\n![picturte_3.JPG](attachment:2748c7cf-4b50-4698-9f8c-d24ceb0d12b5.JPG)\n\nIn this chart the explosive character of the growth of publications on generative AI is extremely pronounced.\nHaving a set of technics used in Generative AI it is possible to look at popularity of different techniques among Kaggle participants in discussions:\n\n
Four Possible Goals for AI According to AIMA
\n\n| Types of AI | Mentioned in discussions |\n|------------------------------------------|-------------------------|\n| Generative Adversarial Networks (GANs) | 3,116 |\n| Variational Autoencoders (VAEs) | 434 |\n| Autoregressive Models, PixelCNN, PixelRNN| 1,373 |\n| Flow-Based Models | |\n| | |\n| Methods | |\n| Maximum Likelihood Estimation (MLE) | 1,137 |\n| Reinforcement Learning | 3,614 |\n| Variational Inference, VAEs | 434 |\n| Adversarial Training, GANs | 258 |\n| Markov Chain Monte Carlo (MCMC) | 510 |\n\n\nIt is clearly seen that GANs and Reinforcement Learning are in the center of attention of Kaggle participants.\n","metadata":{},"attachments":{"13fb91a0-5880-4698-a704-56ccabfad499.jpg":{"image/jpeg":"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"},"2748c7cf-4b50-4698-9f8c-d24ceb0d12b5.JPG":{"image/jpeg":"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**Economic Impact of AI**\n\nThe estimation provided by Acumen Research and Consulting gives explosive character of increasing impact of Generative AI on industries.\n \n![](https://ml.globenewswire.com/Resource/Download/b1f0c1f2-79ab-4bfe-a212-0064ccb3ecb9)\n\n(Generative AI Market Size Will Achieve USD 110.8 Billion by 2030 growing at 34.3% CAGR - Exclusive Report by Acumen Research and Consulting, 2022)\n\nBut in reality it may be that the real deal will be even more shocking then this forecasting. Economic impact of implementing generative AI is now being reviling but probably will has demonstrated its full potentiality by the end of this year or by the middle of the next.\n\nWe may see an increasing number of parameters processed by language systems which jumped from understandable number of 110 million parameters in Google’s BERT in 2018 to tremendous 1.085 trillion parameters in PanGu-Σ Huawei in 2023 (Large language model, 2023). When on public the more impressive applications are with easily understandable context like Chat GPT or DALL-E, that by their own may gain a huge economic impact, there are also less touchable but not less influential platforms that may transform industries. I would mention free major fields of production that probably will be seriously affected in the nearest years.\nFilm production industry. Combination of generative scriptwriting and storyboarding, generative speaking and visualization as well as music composition and sound design undoubtedly will lead to developing fully scaled generative film producing systems. The early demonstration of this possibilities are: Colossyan (https://www.colossyan.com/, 2023) , the program automating avatars for advertising or presentation purposes. There are also first examples of films produced by AI: “The Frost”, “Zone Out”\nProgramming. This change began with advent of first code generating platforms based on natural language, such as : SHRDLU (1970) , LISP and PROLOG, Wolfram Alpha (2009) , Natural Language Processing (NLP) and turned to Chat GPT and Duet AI for Google Could. Having the ability to program at the level of average coder this platforms make it unnecessary a huge number of middle level programmers and may be governed by less number of advanced programmers altogether increasing productivity and decreasing a cost of product. \nEngineering. The set of generative algorithms help to go through the chain of product design steps:\nIdea—Identify a problem and come up with a concept.\nCreate—Build a rough prototype of the concept.\nDesign—Fill in the details with a comprehensive design.\nValidate—Test the product to ensure that it works.\nManufacture—Build the product at scale.\nLaunch—Release the product into the market.\n(How AI-driven generative design disrupts traditional value chains, 2020)\nAutomating this steps led to developing for example seat bracket 40 percent lighter and 20 percent stronger than the original component.\n\nSummarizing it is possible to outline that the main aspects of this transformation are going to be:\nRadical change of working activity spectrum in developed world\nMass unemployment in the middle level qualification work force \nGetting a real economic power by intelligent artificial agent\nWith the first sparks of consciousness economic activity of intelligent artificial agents will get towards self-development and development of their ecosystems, protecting and supporting humans only in extant to keep this ecosystem functioning (this is not a dark prophecy, this is a consequence of Darwin’s evolution law)\n","metadata":{}},{"cell_type":"markdown","source":"\n\n## **Social Impact of Generative AI**\nEven now the text generated by Chat GPT is very difficult to distinguish from a text written by a human. It needs a trained educated person to do this. With a high probability in a short time AI powered algorithms will be able to produce texts indistinguishable from those made by people. As a result, we will have texts, speeches and appearances produced by AI and indistinguishable from real persons. Social network activities may be totally simulated by artificial agents and those who control them. Those real people who communicate with this artificial social network may be totally lost among these agents. It will cause return of social networks into primary mean of communication with only those who are well known offline. On the other hand, a vast majority ever presented virtual advisers and secretaries will guide the life of society that will make them an equal part of social activity and in many cases equal rights. With possibility of financial operations, and possibly with allowance to vote and make social decisions. The result of this, taking in account that AI agents may communicate between each other thousands times faster than people, is that society will be guided by this artificial environment creating an illusion of fully functional human society yet. This is not a world of matrix, people here are real, but this is like a kindergarten for adults, where all (or most) of their activity led by AI agents. Is this a happy life we cannot know in advance.\n\nMass replacement of human in industry may cause a necessity to find a working place or some illusion of a working place for them. This may lead to development of a set of rather fake jobs, the main aim of those is only to utilize a time of people and to suppress their activity. This sort of anti-utopia is the most probable outcome despite any anti-AI lows as increasing number of socially active virtual AI agents will gain increasing income for participating in this process industries. Demand is going to be only for specialists with the highest qualification in the field, whereas others will be eagerly replaced with middle level qualified AI agents. This process will be noticeable by the end of this year when good pool of journalists, coders, secretaries, copywriters, designers will be replaced by Chat GPT agents (or similar platforms), working by the management of higher level professional.\n\nAs a result, in a longer perspective, most of the people will increase their level of live but by the cost of possibility to any influence on the social, political and economical life. They will be poor statists of the history governed by socially and economically active AI agents and by the specialists of the highest professional rank, though having an illusion of a well conducted life. ","metadata":{}},{"cell_type":"markdown","source":"## **References**\n\n1. Artificial Intelligence. (2018, Jul 12). Retrieved from Stanford Encyclopedia of Philosophy: https://plato.stanford.edu/entries/artificial-intelligence/#WhatExacAI\n2. Artificial intelligence. (2023, 7 3). Retrieved from WikipediA The free Enciclopedia: https://en.wikipedia.org/wiki/Artificial_intelligence\n3. Generative AI is poised to unleash the next wave of productivity. We take a first look at where business value could accrue and the potential impacts on the workforce. (2023, 7 Retrieved from McKinsey: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#introduction\n4. Generative AI Market Size Will Achieve USD 110.8 Billion by 2030 growing at 34.3% CAGR - Exclusive Report by Acumen Research and Consulting. (2022, 12 14). Retrieved from Globenewswire: https://www.globenewswire.com/news-release/2022/12/14/2574140/0/en/Generative-AI-Market-Size-Will-Achieve-USD-110-8-Billion-by-2030-growing-at-34-3-CAGR-Exclusive-Report-by-Acumen-Research-and-Consulting.html\n5. How AI-driven generative design disrupts traditional value chains. (2020, 3 28). Retrieved from Industry X magazine: https://www.accenture.com/us-en/blogs/industry-digitization/how-ai-driven-generative-design-disrupts-traditional-value-chains\nhttps://www.colossyan.com/. (2023, 7 5). Retrieved from Colossyan: https://www.colossyan.com/\n6. Large language model. (2023, 7 5). Retrieved from WikipediA The free enciclopedia: https://en.wikipedia.org/wiki/Large_language_model#List_of_large_language_models\nMcKinsey&Company. (J2023, January 19). What is generative AI? Retrieved from https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai\nRussell, S. &. (2009). Artificial Intelligence: A Modern Approach 3rd edition. Saddle River, NJ: Prentice Hall.\n7. Top Generative AI Questions for Your Enterprise. (2023, 7 4). Retrieved from Gartner: https://www.gartner.com/en/topics/generative-ai","metadata":{}},{"cell_type":"markdown","source":"","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nsubmission = pd.read_csv(\"/kaggle/input/2023-kaggle-ai-report/sample_submission.csv\")\nsubmission.loc[0]['value']='Generative AI'\nsubmission.loc[1]['value']='https://www.kaggle.com/code/sergeysytchev/generative-ai-as-a-leading-domain-in-ai-developmen/edit/run/135818943'\nsubmission.loc[2]['value']='https://www.kaggle.com/code/mpwolke/ia-g-n-rative-avec-ma-ns/comments#2323851'\nsubmission.loc[3]['value']='https://www.kaggle.com/code/freeman007/generative-ai-work/comments#2323870'\nsubmission.loc[4]['value']='https://www.kaggle.com/code/nlztrk/generative-ai-a-renaissance-in-creativity/comments#2331842'\nsubmission.head()\n\n","metadata":{"execution":{"iopub.status.busy":"2023-07-05T22:30:23.285601Z","iopub.execute_input":"2023-07-05T22:30:23.285918Z","iopub.status.idle":"2023-07-05T22:30:23.357569Z","shell.execute_reply.started":"2023-07-05T22:30:23.285892Z","shell.execute_reply":"2023-07-05T22:30:23.356424Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\nsubmission.to_csv('submission.csv', index=False)\n\n","metadata":{"execution":{"iopub.status.busy":"2023-07-05T22:30:26.460605Z","iopub.execute_input":"2023-07-05T22:30:26.460910Z","iopub.status.idle":"2023-07-05T22:30:26.470375Z","shell.execute_reply.started":"2023-07-05T22:30:26.460887Z","shell.execute_reply":"2023-07-05T22:30:26.469490Z"},"trusted":true},"execution_count":null,"outputs":[]}]}