Category Archives: Artificial General Intelligence
OpenAI Director Says Artificial General Intelligence May Be 5 Years Out – PYMNTS.com
How long will it take for artificial intelligence to be as smart as human beings?
According to OpenAI board member Adam DAngelo, that milestone is likely to happen within five to 15 years, Seeking Alpha reported Monday (July 29).
DAngelo, CEO and co-founder of Quora, made that prediction during an event last week, the report added. He said the advent of artificial general intelligence (AGI) will be a very, very important change in the world when we get there.
His comments follow reports from earlier this month that OpenAI had developed a way to track its progress toward building AGI, with the company sharing a new five-level classification system with employees.
The company believes it is now at Level 1, where AI that can interact in a conversational way with people, and is approaching Level 2, or systems that can solve problems as well as a human with a doctorate-level education.
The next levels involve AI systems that can spend several days acting on a users behalf, develop innovations, and finally at level five do the work of an organization.
OpenAI CEO Sam Altman and Chief Technology Officer (CTO) Mira Murati said last fall that AGI will be reached within the next 10 years.
Were big believers that you give people better tools, and they do things that astonish you, Altman said. And I think AGI will be the best tool humanity has yet created.
As PYMNTS wrote recently, the reports of these efforts have sparked buzz in the business world of the possibility of AI-powered commerce that could rewrite the rules of global trade, assuming the technology can live up to the hype.
OpenAIs pursuit of human-level reasoning isnt just a technological marvel; its a narrative of pushing boundaries and sparking new possibilities in every sector, Ghazenfer Mansoor, founder and CEO of Technology Rivers, told PYMNTS. In business, AI can dramatically change how supply chains are managed, forecast market trends with great accuracy, and make customer experiences very personal on a big scale.
Earlier this year, OpenAI staffers reportedly showed demos of AI models that could answer tricky science and math questions, with one model scoring more than 90% on a championship math dataset. The company also recently showcased a project with new human-like reasoning skills at an internal meeting.
The way such an algorithm can work is by creating multiple options, following a tree of possibilities, and then reasoning about the outcome and choosing the best path, SmythOS CTO Alexander De Ridder told PYMNTS. This is similar to how chess players think different steps ahead before choosing to move their piece.
He suggested that OpenAIs innovation likely involves an algorithmic breakthrough in how to do this efficiently and scalably, potentially combining autonomous web research and tool usage to arrive at a reasoning breakthrough.
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OpenAI Director Says Artificial General Intelligence May Be 5 Years Out - PYMNTS.com
To understand the perils of AI, look to a Czech novelfrom 1936 – The Economist
When historians in future centuries compile the complete annals of humankind, their output will be divided into two tomes. The first will cover the hundreds of thousands of years during which humans have been earths highest form of intelligence. It will recount how souped-up apes came up with stone tools, writing, sliced bread, nuclear weapons, space travel and the internetand the various ways they found to misuse them. The second tome will describe how humans coped with a form of intelligence higher than their own. How did our sort fare once we were outsmarted? Rather thrillingly, the opening pages of that second volume may be about to be written. Depending on whom you ask, artificial general intelligencesystems capable of matching humans, and then leaving them in the cognitive dustare either months, years or a decade or two away. Predictions of how this might pan out range from everyone enjoying a life of leisure to the extinction of the human race at the hands of paperclip-twisting robots.
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To understand the perils of AI, look to a Czech novelfrom 1936 - The Economist
The exponential expenses of AI development – AI News
Tech giants like Microsoft, Alphabet, and Meta are riding high on a wave of revenue from AI-driven cloud services, yet simultaneously drowning in the substantial costs of pushing AIs boundaries. Recent financial reports paint a picture of a double-edged sword: on one side, impressive gains; on the other, staggering expenses.
This dichotomy has ledBloombergto aptly dub AI development a huge money pit, highlighting the complex economic reality behind todays AI revolution. At the heart of this financial problem lies a relentless push for bigger, more sophisticated AI models. The quest for artificial general intelligence (AGI) has led companies to develop increasingly complex systems, exemplified by large language models like GPT-4. These models require vast computational power, driving up hardware costs to unprecedented levels.
To top it off, the demand for specialised AI chips, mainly graphics processing units (GPUs), has skyrocketed. Nvidia, the leading manufacturer in this space, has seen its market value soar as tech companies scramble to secure these essential components. Its H100 graphics chip, the gold standard for training AI models, has sold for an estimated $30,000 with some resellers offering them for multiple times that amount.
The global chip shortage has only exacerbated this issue, with some firms waiting months to acquire the necessary hardware. Meta Chief Executive Officer Zuckerbergpreviously saidthat his company planned to acquire 350,000 H100 chips by the end of this year to support its AI research efforts. Even if he gets a bulk-buying discount, that quickly adds to billions of dollars.
On the other hand, the push for more advanced AI has also sparked an arms race in chip design. Companies like Google and Amazon invest heavily in developing their AI-specific processors, aiming to gain a competitive edge and reduce reliance on third-party suppliers. This trend towards custom silicon adds another layer of complexity and cost to the AI development process.
But the hardware challenge extends beyond just procuring chips. The scale of modern AI models necessitates massive data centres, which come with their technological hurdles. These facilities must be designed to handle extreme computational loads while managing heat dissipation and energy consumption efficiently. As models grow larger, so do the power requirements, significantly increasing operational costs and environmental impact.
In apodcast interviewin early April, Dario Amodei, the chief executive officer of OpenAI-rival Anthropic, said the current crop of AI models on the market cost around $100 million to train. The models that are in training now and that will come out at various times later this year or early next year are closer in cost to $1 billion, he said. And then I think in 2025 and 2026, well get more towards $5 or $10 billion.
Then, there is data, the lifeblood of AI systems, presenting its own technological challenges. The need for vast, high-quality datasets has led companies to invest heavily in data collection, cleaning, and annotation technologies. Some firms are developing sophisticated synthetic data generation tools to supplement real-world data, further driving up research and development costs.
The rapid pace of AI innovation also means that infrastructure and tools quickly become obsolete. Companies must continuously upgrade their systems and retrain their models to stay competitive, creating a constant cycle of investment and obsolescence.
On April 25, Microsoft said it spent $14 billion on capital expenditures in the most recent quarter and expects those costs to increase materially, driven partly by AI infrastructure investments. That was a 79% increase from the year-earlier quarter. Alphabet said it spent $12 billion during the quarter, a 91% increase from a year earlier, and expects the rest of the year to be at or above that level as it focuses on AI opportunities, the article by Bloomberg reads.
Bloomberg also noted that Meta, meanwhile, raised its estimates for investments for the year and now believes capital expenditures will be $35 billion to $40 billion, which would be a 42% increase at the high end of the range. It cited aggressive investment in AI research and product development,Bloombergwrote.
Interestingly, Bloombergs article also points out that despite these enormous costs, tech giants are proving that AI can be a real revenue driver. Microsoft and Alphabet reported significant growth in their cloud businesses, mainly attributed to increased demand for AI services. This suggests that while the initial investment in AI technology is staggering, the potential returns are compelling enough to justify the expense.
However, the high costs of AI development raise concerns about market concentration. As noted in the article, the expenses associated with cutting-edge AI research may limit innovation to a handful of well-funded companies, potentially stifling competition and diversity in the field. Looking ahead, the industry is focusing on developing more efficient AI technologies to address these cost challenges.
Research into techniques like few-shot learning, transfer learning, and more energy-efficient model architectures aims to reduce the computational resources required for AI development and deployment. Moreover, the push towards edge AI running AI models on local devices rather than in the cloud could help distribute computational loads and reduce the strain on centralised data centres.
This shift, however, requires its own set of technological innovations in chip design and software optimisation. Overall, it is clear that the future of AI will be shaped not just by breakthroughs in algorithms and model design but also by our ability to overcome the immense technological and financial hurdles that come with scaling AI systems. Companies that can navigate these challenges effectively will likely emerge as the leaders in the next phase of the AI revolution.
(Image by Igor Omilaev)
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5 Visionary Leaders Driving Artificial Intelligence in 2024 – CEO Insights Asia
Keerthana Kantharaj, Correspondent
The fast transition to an artificial intelligence-wired (AI) society is thanks to decades of innovation, experimentation and research. At the heart of this progress are some unique visionary leaders in AI. We are talking about a bunch of AI technology leaders at the helm of the transformation stories of many industries. These AI industry leaders are also the ones driving the ethical use of technology in the common mans world. Visionaries driving AI continue setting new standards in the fields of computational intelligence, machine learning and neural networks. Here are top AI visionaries in 2024 spotlighting how their achievements and innovations have paved the way for a technological revolution.
Mustafa Suleyman, Co-Founder, DeepMind & Inflection AI: A Torchbearer in Ethical AI Research
Britain-based computer scientist and entrepreneur Mustafa Suleyman is one of the worlds most well-known names and is at the forefront of the AI boom. During his time as DeepMinds Co-Founder, he left behind a huge trail of ground-breaking algorithms and systems that challenge general intelligence and reinforcement learning. Along with Demis Hassabis and Shane Legg, Suleyman made DeepMind famous for its work in deep learning, especially in the fields of speech and picture recognition. Mustafa has guided teams to implement path-breaking AI systems through Google products and in other industries to showcase the practical application of AI research.
Mustafa has greatly been instrumental in changing the way AI was incorporated into products and ensured the address of moral concerns by lending his expertise to Google's AI policy and product development.
He left DeepMind to focus more on his mission to enhance human-computer connection through his co-founded venture, Inflection AI, in 2022, a company that specializes in "natural language interfaces" and generative AI. Mustafa still plays an active role by continuing to share his experience through writings, talks and board membership in prestigious institutions like The Economist. Today, he stands for the promotion of ethical AI research and its potential advantages for society.
Yoshua Bengio, Co-Founder, Mila: The Coach of Upcoming AI Scientists
One of the fathers of deep learning is the Canadian computer scientist Yoshua Bengio. Yoshua has propelled the advancements in the creation of learning algorithms and neural networks. His research on convolutional neural networks, restricted Boltzmann machines, and deep belief networks are the reasons for the advancement of deep learning and the creation of many of the widely used AI systems today. Many of his write ups, co-authored books and research articles have been a key guide to help shape the conversation and trajectory of deep learning research. Today, he shares his technology wisdom with the upcoming generation of AI scientists.
He co-founded Mila, the Montreal Institute for Learning Algorithms, which is a research institution showcasing his dedication to advancing deep learning research and fostering collaboration. He also shares an interest in voicing out AIs development in a responsible manner, including solving concerns about it. Together with Yann LeCun and Geoffrey Hinton, Yoshua was recognized for the coveted Turing Award or the "Nobel Prize" of computers, in 2018 for groundbreaking work in deep learning.
Yann LeCun, Chief AI Scientist of Meta: A Legendary Mentor for Next Generation AI Researchers
When learning about one of the fathers of AI, it is worth learning about the godfather of AI, Yann LeCun. Yann is renowned for his major contributions to the field of deep learning, specifically in using neural networks to analyze and interpret complicated data. His research plays a heavy part in helping lead the AI revolution by enabling machines to learn and analyze data in ways that were previously unthinkable. One of his most widely known AI works is the creation of convolutional neural networks (CNNs), largely serving applicative value in speech and picture recognition. Besides that, Yann also invented the use of CNNs for image recognition in the 1990s, which sparked advances in the field and allowed computers to accurately identify and categorize images.
In recognition of their ground-breaking work in deep learning, LeCun, Bengio, and Hinton shared the prestigious Turing Award in 2018. Currently, he operates in Meta as the Chief AI Scientist, leading a team and directing the company's AI research and development. One of the companies he founded is the Computational and Biological Learning Lab at New York University, a research group actively exploring frontiers in AI and machine learning. He has also authored or co-authored a number of significant research papers and actively mentors the next generation of AI researchers, sharing his knowledge and expertise.
Dr. Andrew Ng, Co-Founder, DeepLearning.AI & Coursera: Leader in the Ethical Development of AI
Renowned computer scientist and entrepreneur Dr. Andrew Ng is driving the ethical development of AI systems. Dr. Andrew has authored and co-authored over 200 academic articles on robotics, machine learning, and related topics. Leading Google Brain, a research team focused on creating deep learning algorithms; he also oversaw the expansion of Baidu's AI group into a large staff. Dr. Andrew is an ardent supporter of granting everyone access to AI. He created DeepLearning.AI and co-founded Coursera, two of the top online learning platforms, to provide millions of students across the world with free and open-source education. In addition, Ng also started Landing AI, a business that creates SaaS solutions driven by AI, and the AI Fund, which aims to support innovation and invest in potential AI startups.
Ng's impact goes beyond his technical prowess. He was included in the lists of the 100 Most Influential People by Time magazine in 2013, the Most Creative People by Fast Company in 2014, and the Time 100 Most Influential People in AI in 2023. Additionally, he has advised government organizations on matters pertaining to AI and national security and has collaborated extensively with professionals in the field to create moral and responsible AI practices. His work has influenced corporate and governmental policies around artificial intelligence and has helped to create more ethical and responsible methods for developing and using AI. His leadership in the field of artificial intelligence is cemented by his multifarious accomplishments in research, education, and business.
Sam Altman, Co-Founder, OpenAI: A Young Revolutionary Influencing AIs Ethical Development
Sam Altman is a well-known figure in the field of generative AI and co-founder of the popular AI research and deployment group OpenAI. With the introduction of ChatGPT in November of last year, Altman has become a beacon of the AI revolution, and his work on generative AI has been crucial in influencing the direction of AI innovation going forward. A massive tech frenzy was sparked by the generative AI chatbot, which prompted Google and Meta to invest enormous sums of money in the research and development of artificial intelligence.
However, Altman's contribution to igniting the AI revolution goes far beyond developing ChatGPT. Altman has been at the vanguard of numerous innovative AI projects and has been a significant figure in the internet industry for more than ten years. He was the previous president of Y Combinator, a startup accelerator that has assisted in the development of firms like Reddit, Dropbox, and Airbnb. Several AI businesses, notably DeepMind, which Google acquired in 2015 for an alleged $500 million, had Altman as a major investor. In addition, Altman has spoken out against the possible dangers of artificial intelligence and in favor of developing AI in an ethical manner. Additionally, he has supported the use of AI to address some of the most important issues facing the globe, like healthcare and climate change.
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5 Visionary Leaders Driving Artificial Intelligence in 2024 - CEO Insights Asia
Apple agrees to adopt AI safeguards following in footsteps of tech rivals – New York Post
Apple on Friday said it will voluntarily adopt safeguards for artificial intelligence joining other tech giants including OpenAI, Amazon, Google parent Alphabet and Meta in complying with Biden administration guidelines aimed at minimizing national security risk.
In July 2023, the Biden administration announced that it had secured voluntary commitments from seven leading AI companies who pledged to help move toward safe, secure, and transparent development of the technology.
Amazon, Anthropic, Google, Inflection, Meta, Microsoft and OpenAI were the first seven companies to sign on to the administrations initiative.
The companies are asked to transparently share results of tests that measure compliance with security and anti-discrimination regulations.
Apple joined their tech rivals after announcing last month that it would be incorporating AI features into its signature products including iPhone, iPad and Mac.
The Cupertino, Calif.-based colossus announced a fresh set of free software updates dubbed Apple Intelligence in an effort to catch up with other Silicon Valley rivals, such as Microsoft and Google, that have moved ahead of the pack by leaps and bounds in the AI arms race.
At its annual World Wide Developers Conference last month, Apple said it would rely on OpenAIs ChatGPT to make its virtual assistant Siri smarter and more helpful.
Siris optional gateway to ChatGPT will be free to all iPhone users and made available on other Apple products once the option is baked into the next generation of Apples operating systems.
ChatGPT subscribers are supposed to be able to easily sync their existing accounts when using the iPhone, and should get more advanced features than free users would.
Apples full suite of upcoming features will only work on more recent models of the iPhone, iPad and Mac because the devices require advanced processors.
For instance, consumers will need last years iPhone 15 Pro or buy the next model coming out later this year to take full advantage of Apples AI package, although all the tools will work on Macs dating back to 2020 after that computers next operating system is installed.
The rapid advancement of AI technology has prompted debate among tech observers over possible risks posed to the economy, national security and even the survival of the human race.
Last month, a group of AI whistleblowers claimed that Google and OpenAI were endangering humanity as they sprinted to develop the new technology.
Signed by current and former employees of OpenAI, Google DeepMind and Anthropic, the open letter cautioned that AI companies have strong financial incentives to avoid effective oversight and cited a lack of federal rules on developing advanced AI.
Companies are racing to develop and deploy ever more powerful artificial intelligence, disregarding the risks and impact of AI, former OpenAI employee Daniel Kokotajlo, one of the letters organizers, said in a statement.
I decided to leave OpenAI because I lost hope that they would act responsibly, particularly as they pursue artificial general intelligence.
Government and private sector researchers worry US adversaries could use the models, which mine vast amounts of text and images to summarize information and generate content, to wage aggressive cyber attacks or even create potent biological weapons.
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Apple agrees to adopt AI safeguards following in footsteps of tech rivals - New York Post
Why artificial intelligence often struggles with math – The Times of India
In the school year that ended recently, one class of learners stood out as a seeming puzzle. They are hardworking, improving and remarkably articulate. But curiously, these learners - artificially intelligent chatbots - often struggle with math. Chatbots such as Open AI's ChatGPT can write poetry, summarize books and answer questions, often with human-level fluency. These systems can do math, based on what they have learned, but the results can vary and be wrong. They are fine-tuned for determining probabilities, not doing rules-based calculations. Likelihood is not accuracy, and language is more flexible, and forgiving, than math. "The AI chatbots have difficulty with math because they were never designed to do it," said Kristian Hammond, a computer science professor and AI researcher at Northwestern University. The world's smartest computer scientists, it seems, have created AI that is more liberal arts major than numbers whiz. That, on the face of it, is a sharp break with computing's past. Since the early computers appeared in the 1940s, a good summary definition of computing has been "math on steroids." They have been tireless, fast, accurate calculating machines. Yet, all past efforts at AI did hit a wall. Then, over a decade ago, a different approach began to deliver striking gains. The underlying technology, called a neural network, loosely modelled on the human brain began generating language, based on all the information it has absorbed, by predicting what word or phrase is most likely to come next - much as humans do. But at times, AI chatbots have stumbled with simple arithmetic and math word problems that require multiple steps to reach a solution, something recently documented by some technology reviewers. The AI's proficiency is getting better, but it remains a shortcoming. Speaking at a recent symposium, Kristen DiCerbo, chief learning officer of Khan Academy, an education nonprofit that is experimenting with an AI chatbot tutor and teaching assistant, introduced the subject of math accuracy. "It is a problem, as many of you know," DiCerbo told the educators. A few months ago, Khan Academy made a significant change to its AI-powered tutor, called Khanmigo. It sends many numerical problems to a calculator program instead of asking the AI to solve the math. While waiting for the calculator program to finish, students see the words "doing math" on their screens and a Khanmigo icon bobbing its head. "We're actually using tools that are meant to do math," said DiCerbo, who remains optimistic that conversational chatbots will play an important role in education. For more than a year, ChatGPT has used a similar workaround for some math problems. For tasks such as large-number division and multiplication, the chatbot summons help from a calculator program. Math is an "important ongoing area of research," OpenAI said in a statement, and a field where its scientists have made steady progress. Its new version of GPT achieved nearly 64% accuracy on a public database of thousands of problems requiring visual perception and mathematical reasoning, the company said. That is up from 58% for the previous version. The technology's erratic performance in math adds grist to a spirited debate in the AI community about the best way forward in the field. Broadly, there are two camps. On one side are those who believe that the advanced neural networks, known as large language models, that power AI chatbots are almost a singular path to steady progress and eventually to artificial general intelligence, or AGI, a computer that can do anything the human brain can do. That is the dominant view in much of Silicon Valley. But there are skeptics who question if adding more data and computing power to the large language models is enough. Prominent among them is Yann LeCun, chief AI scientist at Meta. The large language models, LeCun has said, have little grasp of logic and lack common-sense reasoning. What's needed, he insists, is a broader approach, which he calls "world modelling," or systems that can learn how the world works much as humans do. And it may take a decade or so to achieve.
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Why artificial intelligence often struggles with math - The Times of India
The Future That AI Can Help Build – American Enterprise Institute
When will the future arrive? Of course, thats a nonsense question. The future isnt a fixed point that suddenly arrives. Time flows continuously, and were always moving from today into tomorrow. As soon as a moment arrives, it becomes the present, and then immediately becomes the past. Rather than a destination even one with flying cars and mile-high skyscrapers the future is a continuous process of experiencing each new moment as it comes. Kind of a brain-bender, I know.
A better version of that question: When will the sorts of technological advancements that we often think of as futuristic finally happen? As the saying, (attributed to many different folks) goes, It is difficult to make predictions, especially about the future.
That caveat noted, here are some current consensus predictions from the Metaculus forecasting platform:
That last forecast is particularly interesting to me since it suggests how forecasts can affect each other. For example: If the forecast for the date of artificial general intelligence or superintelligence were moved forward, it should prompt forecasters to reconsider timelines for other tech advancements like cancer cures or nuclear fusion. That, especially if forecasters believe AGI could accelerate research and development in those areas.
Which they absolutely should. Indeed, the potential impact on accelerating scientific and tech progress is a big part of the bullish case for AGI and the economy although one ignored by most economic forecasters on Wall Street and in Washington.
Take the recent debate between economist Daron Acemoglu and Goldman Sachs about the economic impact of AI.The crux of the disputeis their differing assumptions about AIs potential for task automation, as well as Goldmans inclusion of labor reallocation and new job creation in its analysis. These are factors Acemoglu doesnt account for in his more pessimistic prediction. Butneitherof them includes the potential impact of radical tech breakthroughs, something tough to model.
As Acemogluputs it:
I also do not discuss how AI can have revolutionary effects by changing the process of science (a possibility illustrated by neural network-enabled advances in protein folding and new crystal structures discovered by the Google subsidiary DeepMind), because large-scale advances of this sort do not seem likely within the 10-year time frame and many current discussions focus on automation and task complementarities.
But in this newsletter, I like to consider what Acemoglu calls revolutionary effects. And so does computer science and inventor Ray Kurzweil, author of the booksThe Age of Spiritual Machines(1999) andThe Singularity is Near(2005). His new book,The Singularity is Nearer: When We Merge with AI, will be published on June 25th. In anessayfor the new issue of The Economist, Kurzweil does a great job of outlining how AI will affect other aspects of science and technology:
Kurzweil:
By the time children born today are in kindergarten, artificial intelligence (ai) will probably have surpassed humans at all cognitive tasks, from science to creativity. When I first predicted in 1999 that we would have such artificial general intelligence by 2029, most experts thought Id switched to writing fiction. But since the spectacular breakthroughs of the past few years, many experts think we will have AGI even soonerso Ive technically gone from being an optimist to a pessimist, without changing my prediction at all.
The techno-optimist highlights three key areas to showcase AIs transformative potential:
The Kurzweil kicker: This is AIs most transformative promise: longer, healthier lives unbounded by the scarcity and frailty that have limited humanity since its beginnings.
As I see it, the real value in what Kurzweil is saying isnt its predictive power or insights into AI timelines but rather the Up Wing image of the future it suggests. A big theme of my bookThe Conservative Futuristis the importance of having positive images of the future. They are crucial for societal progress and human flourishing. From the book:
American historian Carl Becker notes in his 1936 book Progress and Power that a Philosopher could not grasp the modern idea of progressuntil he was willing to abandon ancestor worship, until he analyzed away his inferiority complex toward the past, and realized that his own generation was superior to any yet known.
The ancient Greeks, for instance, conceived of the future in a fundamentally different way than the modern West. My Hellenic ancestors didnt face the future to see what was coming. They instead metaphorically had their backs turned to the future and faced the past, viewing what had already happened as a guide to what might happen next.
But in the two centuries between Columbus sailing to the New World and the death of Isaac Newton in 1727, doubts arose about the wisdom of the ancients. If the natural philosophers of the past didnt know about the vast continent and peoples across the Atlantic or about gravity, what else might they not have known or gotten wrong? This newfound skepticism helped power the Scientific Revolution, the Enlightenment, and the rise of an Up Wing culture among the literate elite of Europeastronomers, chemists, clergymen, doctors, engineers, mathematicians.
Dutch futurist Frederik Polak argued that cultures without optimistic visions of tomorrow lack direction and vitality. Positive future images inspire innovation, drive scientific and tech advancements, and motivate people to work towards better outcomes. Without such visions, we risk stagnation or decline. And Kurzweil just gave us a pretty compelling vision. Hope to see more of them. Faster, please!
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The Future That AI Can Help Build - American Enterprise Institute
Railtown AI Unveils Version 2.0 of Conductor | RLAIF Stock News – StockTitan
Railtown AI Technologies has launched Conductor Version 2.0, an advanced AI platform designed to transform how companies manage their software applications. This release aims to provide a holistic view of application performance and development processes by integrating and analyzing diverse application data. Key features include integrated data analysis, comprehensive application overviews, and advanced insights, offering actionable recommendations to enhance efficiency and reliability. According to CTO Marwan Haddad, this version marks a significant step toward building an Artificial General Intelligence for managing software application lifecycles. Conductor Version 2.0 is available to all current and new customers.
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Vancouver, British Columbia--(Newsfile Corp. - July 2, 2024) - Railtown AI Technologies Inc. (CSE: RAIL) (OTCQB: RLAIF) ("Railtown AI'', "Railtown" or the "Company") is pleased to announce the launch of Conductor Version 2.0, an advanced AI platform that is transforming how companies build and manage their software applications.
Conductor Version 2.0 is designed to drive new insights by seamlessly aggregating and analyzing diverse application data. By providing a holistic view of application performance and development processes, Railtown AI enables organizations to understand all aspects of their software applications. This enhanced perspective is a crucial step toward the company vision of building an Artificial General Intelligence (AGI) that manages and controls all aspects of the software application lifecycle.
"Our mission with Railtown AI has always been to empower businesses with actionable intelligence," said Marwan Haddad, CTO at Railtown AI. "With the release of Version 2.0, we're taking a giant leap forward by giving companies the tools they need to not only monitor but also optimize every aspect of their application ecosystem. This is more than just an update; it's a transformation in how we understand and manage software."
Key features of Conductor Version 2.0 include:
Conductor Version 2.0 is now available to all current and new customers.
About Railtown AI Technologies
Railtown AI, a Microsoft Partner, is a cloud-based Application General Intelligence Platform for Software Developers and Teams that practice Agile Project Management. We purposely built our Application General Intelligence Platform to help Software Developers and Agile practitioners save time on redundant tasks, improve productivity, drive down costs, and accelerate developer velocity. Railtown's proprietary AI technology, designed to enable our clients to be more productive and profitable, is accessible on Microsoft's Azure Marketplace.
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This news release contains forward-looking statements relating to the future operations of the Company and other statements that are not historical facts. Forward-looking statements are often identified by terms such as "will," "may", "should", "intends", "anticipates", "expects" and similar expressions. All statements other than statements of historical fact included in this release, including, without limitation, statements regarding the future plans and objectives of the Company are forward-looking statements that involve risks and uncertainties. There can be no assurance that such statements will prove to be accurate and actual results and future events could differ materially from those anticipated in such statements. Important factors that could cause actual results to differ materially from the Company's expectations are risks detailed from time to time in the filings made by the Company with securities regulators.
Readers are cautioned that assumptions used in the preparation of any forward-looking information may prove to be incorrect. Events or circumstances may cause actual results to differ materially from those predicted, as a result of numerous known and unknown risks, uncertainties, and other factors, many of which are beyond the control of the Company. As a result, the Company cannot guarantee that any forward-looking statement will materialize, and readers should not place undue reliance on any forward-looking information. Such information, although considered reasonable by management at the time of preparation, may prove to be incorrect and actual results may differ materially from those anticipated. Forward-looking statements contained in this news release are expressly qualified by this cautionary statement. The forward-looking statements contained in this news release are made as of the date of this news release and the Company will only update or revise publicly any of the included forward-looking statements as expressly required by Canadian securities law.
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Conductor Version 2.0 is an advanced AI platform designed to transform how companies manage and monitor their software applications through integrated data analysis, comprehensive overviews, and actionable insights.
Conductor Version 2.0 was launched on July 2, 2024.
Key features include integrated data analysis, comprehensive application overviews, and advanced insights with actionable recommendations to enhance software efficiency and reliability.
Customers benefit from a holistic view of application performance, deeper analytical insights, and actionable recommendations that help optimize their software applications.
Yes, Conductor Version 2.0 is available to both current and new customers.
Railtown AI aims to build an Artificial General Intelligence capable of managing all aspects of the software application lifecycle.
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Railtown AI Unveils Version 2.0 of Conductor | RLAIF Stock News - StockTitan
Hollywood tycoon Ari Emanuel blasts OpenAI’s Sam Altman, fearing the future after Elon Musk tells him he’ll become ‘a … – Fortune
As CEO of OpenAI, Sam Altman wants to make history by developing the worlds first artificial general intelligence, or AGIa machine powerful enough to think and reason like a human. But some are starting to worry whether he can be trusted not to accidentally create an AI overlord that views humans as a lower life form.
Speaking this weekend at the Aspen Ideas Festival, media tycoon Ari Emanuel recalled a conversation he had with Elon Musk, a former director of his billion-dollar entertainment company, Endeavor.
The anecdote highlighted the awesome stakes involved as companies race to build ever-smarter neural networks.
Elon said to me oncethis scared mehe said: You know, Ari, your relationship with your dogs? Think about it the following way: Youre the dog to the AI, Emanuel told the audience. I dont want to be a dog.
AI experts such as Geoffrey Hinton fear Silicon Valley executives wont stop at just AGI: Mankind could ultimately create an artificial superintelligence (ASI).
This ASI would not just mimic human learning processes like current transformer-based neural networks such as OpenAIs GPT-4, but could potentially gain self-awareness in the processrelegating humanity to the second-most advanced species on earth.
With so much riding on Altmans ability to make the responsible decision, Emanuel fears past behavior suggests he cant be trusted to properly develop groundbreaking technologyespecially given a growing chorus of critics.
I think hes a con man, said Emanuel. Elon gave him a lot of moneyit was supposed to be a nonprofit, now hes making a lot of money. I dont know why I would trust him. I dont know why we would trust these people. (According to legal filings, Musk contributed more than $44 million into OpenAI between 2016 and September 2020.)
Emanuel said Altman has not done enough to prove the technology doesnt pose a long-term threat to society, especially since the latter seems to prioritize commercialization over safety.
Youre telling me youve done the calculation, and the good outweighs the bad, said Emanuel, whose media business could be hurt by generative AI such as OpenAIs Sora. Really? I dont think so.
OpenAI did not respond to a request fromFortunefor comment.
For his part Altman, who has in the past stated offering equity was necessary in part to attract and retain talent, himself said a year ago that people should not place their trust in any one AI company or CEO without evidence that trust is deserved.
The OpenAI bosswho is worth $2 billion according to Bloombergsurvived aboardroom mutinyin November thanks in part to Microsoft CEO Satya Nadella, and returned more powerful than everwith three of the four former plotters against him leaving the company.
One of those former directors, Helen Toner, in Mayjustified the coupby citing a pattern of dishonest behavior, saying Altman would withhold information, misrepresent things, and sometimes even outright lie to the board.
At the same time, scientists at OpenAI such as Jan Leikeleft the companyafter accusing Altman ofbreaking a key promiseto fund his research. Leike and chief scientistIlya Sutskeverwere supposed to design safety protocols robust enough to ensure AI cannot ever gain the upper hand over humans.
Altman himself is now mingling his commercial responsibility as CEO with anew roleheading up AI safety at the companyraising eyebrows from a governance perspective.
Twitter founder Jack Dorsey has alsosounded the alarm, warning the damage done to human behavior by the very engagement-focused algorithms he himself helped to create could pale when compared with artificial intelligence.
All of this has given Emanuel pause about the AI future.
I dont want to stifle innovation, because I do think we need AI, but we have to have the rails around it, Emanuel said in Aspen this weekend, where Altman was also speaking. What is society going to be like in that world when theres no purpose?
The younger brother of Rahm Emanuelformer chief of staff to President Barack ObamaAri Emanuel is often referred to as a Hollywood super agent having represented stars like Martin Scorsese, but hes an entrepreneur in every sense of the word.
In 1995, the senior partner at talent reps International Creative Management founded Endeavor Agency, transforming it into a fully-fledged media and entertainment empire that went public on the stock exchange in April 2021.
Among his close friends and business associates he counts Hollywood star Dwayne The Rock Johnson, UFC boss Dana White, and Tesla CEO Elon Musk, who briefly served as a director on Endeavors board.
Emanuelplayed hostto the powerful tycoon in Greece, when unflattering pictures of Musk emerged next to a leaner Emanuel. The images prompted so much online ridicule that Musk reportedly began taking Wegovy just tolose the fat.
Altman and Musk, on the other hand, are far from cozy. Despite cochairing OpenAI at its inception in 2015, Musk departed the organization in 2018. Since then a war of wordsand productshas ensued, with the Tesla CEO attempting to sue OpenAI earlier this year.
Emanuel is widely lauded by his Hollywood peers: Theres no CEO in the world like this guy, the Rock said of Emanuel inJanuary.
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ChatGPT could be facing some serious competition: Amazon is reportedly working on a new AI tool, ‘Metis’, to … – ITPro
Amazon is reportedly working on development of a new AI tool aimed at directly competing with ChatGPT as the tech giant looks to compete with the popular chatbot.
According to reports from Business Insider, the internal project, codenamed Metis, is designed to be accessible for users via web browser.
Metis will work in a similar fashion to ChatGPT, providing users text and image-based answers in response to user queries. The chatbot will also reportedly provide links within answers to give users access to source materials used when generating a response, and even suggest follow-up queries.
Sources told the publication the chatbot will be powered by Amazons internal AI model, dubbed Olympus, which is also believed to be in development. Reports on Olympus emerged late last year, but as of yet no concrete details have been teased by the firm.
Development of the chatbot is being led by Amazons artificial general intelligence (AGI) team, which is also working on the Olympus model, and the launch of the service could come in September to coincide with Amazons Alexa event.
A key differentiator for Metis, sources suggested, is that retrieval augmented generation (RAG) will play a big role in optimizing how the chatbot produces responses.
RAG has become the latest industry buzzword amidst a flurry of AI activity over the last 18 months. This allows AI models to draw upon larger knowledge repositories such as organization-specific information, alongside user input, to inform their responses.
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All told, this provides more relevant results for user queries. Metis will be no different, and will be able to source information beyond the original data used to train its supporting model, thereby providing more up-to-date responses.
Sources close to the matter told Business Insider the chatbot will be able to share the latest stock prices in real-time, for example.
Amazon plans appear to also point toward Metis acting as an AI agent. These custom chatbots essentially automate and perform tasks on behalf of the user, and are built using existing, internal data. Sources told BI that some use-cases included booking flights, or turning on lights, pointing toward close integration with Alexa.
Alongside RAG, AI agents have emerged as a major enterprise focus so far in 2024.
Google Cloud launched its own AI Agents service for Vertex AI at Google Cloud Next 2024. Microsoft-backed OpenAI also launched its marketplace for AI agents which allows users to create custom GPTs in a move earlier this year.
Rory Bathgate
Rory Bathgate is Features and Multimedia Editor at ITPro, overseeing all in-depth content and case studies. He can also be found co-hosting the ITPro Podcast with Jane McCallion, swapping a keyboard for a microphone to discuss the latest learnings with thought leaders from across the tech sector.
To compete with the likes of Microsoft and Google, Amazon faces a challenge on several fronts.
Breaking through and capturing customers in this environment will require Metis to deliver serious results. With Metis reportedly powered by Olympus, the tool carries potential to not only produce powerful outputs but also show off Amazons own in-house development capabilities.
That said, its a hard task. In the eight months since rumors about Olympus first surfaced, the AI space has moved on considerably. Gemini 1.5 Pro and GPT-4o continue to push the limits of large language models (LLMs) and unless Olympus is proven to outperform these competitors by sizable margins it could fail to catch the attention of would-be customers.
Rising capabilities of open source models like Metas Llama 3, which cost nothing and are already available on AWS, Azure, and Google Cloud, could also prove a hindrance here. Simple benchmark scores are no longer enough in a world where completely free models can go toe-to-toe with those made by the best AI developers.
Theres also the issue of convenience. Its likely that as AI becomes more commonplace, businesses will choose their AI assistant that requires the least upheaval of their existing stack and as little staff retraining as possible. For example, an organization thats already heavily invested in the Microsoft ecosystem could easily adopt Copilot versus another AI solution.
All of this said, its in its RAG-based approach that Metis could make the most difference. Still considered a novel technique, RAG provides assurances of accuracy that can put fears over hallucinations to bed and make AI adoption much more feasible for enterprises.
If Amazon can sell this message Metis is more reliable than the next best tool it could seize the corner of the market that the company has thus far failed to make gains within.
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