Category Archives: Ai
MongoDB Embraces AI & Reduces Developer Friction With New Features – Forbes
MongoDB
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Even if you havent heard of MongoDB, odds are good that you touch it in your daily online life. MongoDB has enabled more than 43,000 organizations to build solutions leveraging MongoDB technology, including some of the biggest names in technology, healthcare, telecom, and financial services. The company's horizontal document-oriented (often called NoSQL) database technology underpins a broad swath of workloads that all need modern data services needs that often dont directly map to the constraints of traditional relational databases.
Servicing the quickly evolving needs of modern application development requires rapid innovation and fast product cycles. MongoDB demonstrated both last week at its MongoDB.local 2023 event in New York City, introducing a compelling set of new features and services.
The announcements cover a wide breadth of territory, with new capabilities to leverage the latest AI technology, features that enable greater developer productivity, ease the burden of enterprise application development, and even a new program to simplify deploying MongoDB technology into a targeted set of verticals. There's a lot to delve into.
Its impossible to talk about application development today without touching on artificial intelligence. Generative AI, typified by large language models (LLMs) such as ChapGPT, capture headlines daily. The question technology companies and IT practitioners alike most often ask me is how AI will affect them. MongoDB this past week illustrated how generative AI impacts the data plane.
Technologies such as generative AI changes how we think about managing the data that feeds AI-driven systems. Language processing, for example, utilize attributes on data called "vectors."
You can think of vector embeddings as tags placed on data as an AI model that define the relationship between words. These vectors are then used as efficient shortcuts when running generative AI models (this is a simplistic explanation of vectors; interested readers should read this more in-depth explanation).
MongoDB's new MongoDB Atlas Vector Search is designed to simplify the development of AI language and generative AI applications. The new capability allows vector embedding directly on data stored by MongoDB, allowing new generative AI applications to be quickly and efficiently developed on MongoDB Atlas.
MongoDB Vector Search
MongoDB
MongoDB Atlas Vector Search is also integrated with the open-source LangChain and LlamaIndex frameworks with tools for accessing and managing LLMs for various applications.
Building and deploying applications leveraging the latest in AI technology can be daunting. The concepts, tools, and even infrastructure significantly differ from more traditional software development approaches. AI applications can also require multiple iterations of model training as the application evolves, adding significant development costs.
Last week, recognizing the unique challenges of developing AI applications, MongoDB announced its new MongoDB AI Innovators Program, designed to ease the unique burdens of developing AI applications. The new program offers several benefits, including providing eligible organizations with up to $25,000 in credits for MongoDB Atlas.
The AI Innovators Program also includes engagement opportunities with MongoDB to fast-track strategic partnerships and joint go-to-market activities with what the company calls its AI Amplify track. Companies participating in AI Amplify track have their submissions evaluated by MongoDB to gauge the appropriateness of a potential partnership. MongoDB technical experts are also available for solutions architecture and to help identify compelling use cases to use in co-marketing opportunities.
Finally, MongoDB is making its partner ecosystem available to program participants. Organizations participating in the MongoDB AI Innovators Program will have prioritized access to opportunities with MongoDB Partners, and eligible organizations can be fast-tracked to join the MongoDB Partner Ecosystem to build seamless, interoperable integrations and joint solutions. MongoDB has over 1,000 partners, making this an attractive benefit of the program.
In addition to the new vector search capabilities already mentioned, there were four additional capabilities introduced into MongoDB Atlas:
Keeping with its theme of simplifying the developer experience, these new features should ease the burden of developing applications using MongoDB Atlas as an intelligent data platform.
MongoDB is a foundational component for data modernization, but it is only part of the solution. Mongo recognizes this, calling its technology a Developer Data Platform. The phrase emphasizes the importance of empowering developers to build next-generation AI-enabled applications, often while also using AI. MongoDB empowers developers by delivering a data plane offering the capabilities most needed for modern applications.
Mongo announced new programming language support to facilitate adoption across multiple environments. The company added support for server-side Kotlin applications (Kotlin is a programming language designed for cross-platform application development). There is also new support for data processing and analytics with Python as MongoDB makes its open-source PyMongoArrow library generally available, allowing developers to efficiently convert data stored in MongoDB using some of the most popular Python-based analytics frameworks.
MongoDB is also adding additional support for deploying and managing MongoDB using Amazon AWS infrastructure-as-code (IaC) capabilities. MongoDB released a new integration with the AWS Cloud Development Kit (CDK), allowing developers to manage MongoDB Atlas resources with C#, Go, Java, and Python. This is a significant enabler for developers deploying on AWS.
MongoDB also simplified its Kubernetes integration with improvements to its MongoDB Atlas Kubernetes Operator. The new functionality allows developers to install MongoDBs horizontal document-oriented (often called NoSQL) database technology underpins a broad swath of workloads that all need modern data services needs that often dont directly map to the constraints of traditional relational databases.
Finally, MongoDB announced its new MongoDB Relational Migrator tool. The new tool makes migrating from traditional legacy databases into a MongoDB environment easier and significantly faster. MongoDB Relational Migrator analyzes legacy databases, automatically generates new data schema and code, and then executes a seamless migration to MongoDB Atlas without downtime. This capability will reduce the pain often experienced when moving data into a new environment from a legacy data store.
MongoDB held an investor conference parallel to its developer-focused MongoDB.local event. At the investor event, MongoDB's chief product officer, Sahir Azam, described how the company builds its product strategy and GTM activities around its understanding of the customer's journey.
The features, and new business opportunities, announced by MongoDB make sense to anyone familiar with the development of a modern data-driven application. The new offerings help developers leverage MongoDB technology to create new applications while also implementing the features required to develop next-generation AI-enabled solutions.
Theres no question that developers appreciate what the company is delivering. As an enabling technology for other applications, MongoDB's approach not only makes sense, it's also necessary. Its also paying off.
MongoDB has beaten consensus estimates in its earnings for seventeen straight quarters, with its most recent earnings besting EPS estimates by nearly 195%. The most recent quarter also saw Mongo growing its top-line revenue by 29% year-over-year. The company has increased revenue by 8x since 2018. That's a tremendous vote of confidence from its customers, especially in a market thats still hampering growth for nearly every foundational technology company.
MongoDB competes in a crowded segment, and we see innovation coming from its closest competitors, evidenced by recent announcements from competitors such as Elastic. At the same time, MongoDB stands out in this intensely competitive environment with its relentless focus on improving the experience for developers, quickly adapting to new trends in data analysis and AI, and implementing programs that allow its customers to launch new applications quickly. Seventeen straight earnings beats, over a thousand partners, and more than 43,000 customers all show that MongoDB is earning its success.
Disclosure: Steve McDowell is an industry analyst, and NAND Research an industry analyst firm, that engages in, or has engaged in, research, analysis, and advisory services with many technology companies, which may include those mentioned in this article. Mr. McDowell does not hold any equity positions with any company mentioned in this article.
Steve McDowell is principal analyst and founding partner at NAND Research.Steve is a technologist with over 25 years of deep industry experience in a variety of strategy, engineering, and strategic marketing roles, all with the unifying theme of delivering innovative technologies into the enterprise infrastructure market.
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MongoDB Embraces AI & Reduces Developer Friction With New Features - Forbes
Why smart AI regulation is vital for innovation and US leadership – TechCrunch
Image Credits: Dragon Claws / Getty Images
As a teenager, I immersed myself in science fiction. While the visions of many films and novels havent come to pass, Im still amazed by legendary writer Isaac Asimovs ability to imagine a future of artificial intelligence and robotics. Now, amid all the hype around generative AI and other AI tools, its time for us to follow Asimovs lead and write a new set of rules.
Of course, AI rules for the 21st century wont be quite as simple as Asimovs three rules of robotics (popularized in I, Robot). But amid anxiety around the rise of AI tools and a misguided push for a moratorium on advanced AI research, industry can and should be pushing for rules for responsible AI development. Certainly, the past centurys advances in technology have given us plenty of experience in evaluating both the benefits of technological progress and the potential pitfalls.
Technology itself is neutral. Its how we use it and the guardrails we set up around it that dictate its impact. As humans, harnessing the power of fire allowed us to stay warm and extend food storage time. But fire can still be destructive.
Think of how the recent Canadian wildfires threatened lives and property in Canada and damaged U.S. air quality. Nuclear power in the form of atomic bombs killed thousands in Japan during WWII, but nuclear energy lights up much of France and powers U.S. aircraft carriers.
In the case of AI, new tools and platforms can solve big global problems and create valuable knowledge. At a recent meeting of Detroit-area chief information officers, attendees shared how generative AI is already speeding up time-to-market and making their companies more competitive.
Generative AI will help us listen to different animal species. AI will improve our health by supporting drug discovery and disease diagnosis. Similar tools are providing everything from personalized care for elders to better security for our homes. More, AI will improve our productivity, with a new study by McKinsey showing generative AI could boost the global economy by $4.4 trillion annually.
With all this possibility, can such an amazing technology also be bad? Some of the concerns around AI platforms are legitimate. We should be concerned about the risk of deep fakes, political manipulation, and fraud aimed at vulnerable populations, but we can also use AI to recognize, intercept and block harmful cyber intrusions. Both barriers and solutions may be difficult and complex, and we need to work on them.
Some may also be simple; we already see schools experimenting with oral exams to test a students knowledge. Addressing those issues head-on, rather than sticking our heads in the sand with a pause on research that would be impossible to enforce and ripe for exploitation by bad actors, will position the United States as a leader on the world stage.
While the U.S. approach to AI has been mixed, other countries seem locked in to a hyper-regulatory stampede. The EU is on the precipice of passing a sweeping AI Act that would require companies to ask permission to innovate. In practice, that would mean that only the government or huge companies with the finances and capacity to afford the certification labyrinth covering privacy, IP, and a host of social protection requirements could develop new AI tools.
A recent study from Stanford University also found that the EUs AI Bill would bar all of the currently existing large language models, including OpenAIs GPT-4 and Googles Bard. Canadian lawmakers are moving forward an overly broad AI bill that could similarly stifle innovation. Most concerning, China is rapidly pursuing civil and military AI dominance through massive government support. More, it has a different view of human rights and privacy protection that may help its AI efforts but is antithetical to our values. The U.S. must act to protect citizens and advance AI innovation or we will be left behind.
What would that look like? To start, the U.S. needs a preemptive federal privacy bill. Todays patchwork of state-by-state rules means that data is treated differently each time it crosses an invisible border causing confusion and compliance hurdles for small businesses. We need a national privacy law with clear guidelines and standards for how companies collect, use, and share data. It would also help create transparency for consumers and ensure that companies can foster trust as the digital economy grows.
We also need a set of principles around responsible AI use. While I prefer less regulation, managing emerging technologies like AI requires clear rules that set out how this technology can be developed and deployed. With new innovations in AI unveiled almost daily, legislators should focus on guardrails and outcomes, rather than attempting to rein in specific technologies.
Rules should also consider the level of risk, focusing on AI systems that could meaningfully hurt Americans fundamental rights or access to critical services. As our government determines what good policy looks like, industry will have a vital role to play. The Consumer Technology Association is working closely with industry and policymakers to develop unified principles for AI use.
Were at a pivotal moment for the future of an amazing, complex and consequential technology. We cant afford to let other countries take the lead.
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Why smart AI regulation is vital for innovation and US leadership - TechCrunch
Generation AI: It is Indias time to play chief disruptor | Mint – Mint
Rapid advancements in Generative Artificial Intelligence (AI) and in its ability to mimic human intelligence to write computer code and much more have caught us all by surprise. We have seen and lived through many technology shifts, but few as significant as this one. Jensen Huang, CEO of Nvidia, summed it up as the most powerful democratization source we have ever seen. A tool for engineers and coders till now, today you dont need to know any of the programming languages to use AI tools. A simple prompt in English is enough.
Rapid advancements in Generative Artificial Intelligence (AI) and in its ability to mimic human intelligence to write computer code and much more have caught us all by surprise. We have seen and lived through many technology shifts, but few as significant as this one. Jensen Huang, CEO of Nvidia, summed it up as the most powerful democratization source we have ever seen. A tool for engineers and coders till now, today you dont need to know any of the programming languages to use AI tools. A simple prompt in English is enough.
As per Goldman Sachs, the right use of Generative AI can add around $7 trillion to the global GDP in the next decade. In a world faced with slowing economic growth, we must invest in technologies that aid growth and productivity, solve complex problems like climate change, and create a more inclusive society. However, this needs to be done with the right guard-rails.
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As per Goldman Sachs, the right use of Generative AI can add around $7 trillion to the global GDP in the next decade. In a world faced with slowing economic growth, we must invest in technologies that aid growth and productivity, solve complex problems like climate change, and create a more inclusive society. However, this needs to be done with the right guard-rails.
India today has the opportunity to provide much-needed thought leadership globally on Generative AI. Our proven track record of creating inclusive technology for societal impact at scale, be it UPI for financial inclusion or Diksha for education, provides a framework to create open, interoperable and affordable platforms for services and products that can be scaled exponentially. Can we build on these learnings and envision it as a strategic inflection point for India to lead the world into an era of Augmented Intelligence? India sowed the seed for it when we designed our national AI strategy to enable AI for All in 2019. Since then, initiatives across government, industry and startups have focused on the inclusive and responsible adoption of AI.
India now needs to prioritize a comprehensive Generative AI strategy on top of its AI foundation to drive breakthrough productivity gains across all aspects of life, business and society. If leveraged right, we can embed a foundational layer of intelligence in every product, service and process, significantly boosting overall productivity. To achieve this, we recommend a four-pronged approach that brings together diverse stakeholders and is enabled by strong execution.
First, real competitive differentiation will be about talent and skills. While India ranks first in AI skills penetration as per the OECD, we need to move the narrative from AI talent to Generation AI. Can we unlock the full potential of Indias demographic dividend and its propensity to technology adoption by creating a generation of AI-literate citizens who know how to use it responsibly? For this, we recommend a tiered strategy:
For few: Aim to become the world leader in data and AI skills by training 1 million world-class AI professionals to meet global demand in areas such as Natural Language Processing, Large Language Models, responsible AI, and data fundamentals.
For many: Empower an 18-20 million workforce to use AI tools for enhanced productivity across sectors. Provide training in domain fundamentals, AI tool usage and responsible AI.
For all: India needs AI literate citizens who constitute an entire generation of AI users equipped with skills and capabilities to unlock its potential across all aspects of life. Provide education in AI application security, AI awareness and responsible AI.
Second, for innovation to thrive, we need to build the infrastructure needed for a globally competitive AI ecosystem. An AI boom depends on three things: large amounts of data, mega computing power to process it, and budgets to afford it. India must invest in building its capabilities, including:
Foundation models: Invest in the development and promotion of large trustworthy AI models that will address our language diversity and our cultural context.
Computing access: Set up a national GPU Cloud with at least Exaflop AI capacity and around 25,000 A100 GPUs or above. This could be done by the government in partnership with industry players by setting up such infrastructure under incentive programmes and recovering the running cost from users over, say, a 10-year period, with subsidized pricing for Indian academia and startups.
Special economic AI clusters: Create virtual AI clusters for core sectors like healthcare, agriculture, energy, manufacturing, defence, etc, to turbocharge innovation and product development. Each cluster could provide access to foundation models and the GPU cloud as well as access to patient capital, fast-track patent approvals, mentorship, and industry links.
Third, India should drive scalable adoption of AI across sectors. We should build a responsible AI stack with our know-how to accelerate adoption across core sectors. India should also set up a sand-box for responsible usage cases.
Lastly, we need a pro-innovation policy formulation that catalyses responsible and ethical AI usage and creation. India should develop a tailored approach that aligns existing laws, identifies gaps and establishes a governance framework to manage risk and foster innovation. This will help protect us against potential harm while driving our advancement and economic growth.
While the world worries about what AI could do, we believe India can and must show what AI should do as a force for good. With our young talent, tech know-how and a strong commitment to leverage technology as an equalizer, India must lead a global shift from Artificial Intelligence to HumanCentric Augmented Intelligence that is designed to make the world better.
Debjani Ghosh is president of Nasscom.
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Generation AI: It is Indias time to play chief disruptor | Mint - Mint
Bets on A.I. and innovation help this tech-focused T. Rowe Price … – CNBC
While attending Colby College in the late 1990s, Ken Allen spent half his time shooting hoops and the other half devoted to day trading. Torn when the time came to search for a job, the economics major first consulted a mentor who connected him with a former student. That connection led the Maine native to T. Rowe Price in Baltimore. Since joining investment management firm in 2000, Allen's worked his way up the corporate ladder, taking the helm as portfolio manager of the T. Rowe Price Science & Technology (PRSCX) fund in 2009. The growth fund launched in 1987 aims to capitalize on innovation. In the wake of the latest artificial intelligence boom that's driven up last year's beaten-up technology stocks, it's skyrocketed nearly 38% in 2023. Longer-term, the fund, with a 0.84% expense ratio, offers 10- and 15-year trailing returns of more than 16% and about 13%, respectively. PRSCX YTD mountain PRSCX shares in 2023 Key to Allen's strategy since he began running the more than $7-billion fund is finding stocks he views as undervalued, hinging his investment framework around an analysis of cash flows. Allen also views solid, independent research as critical pieces of his methodology. This year, Allen has benefited from a spectacular run-up in technology stocks, fueled by a mania for all things tied to artificial intelligence. That said, "I try to stay really disciplined around valuation," Allen maintains. "I think especially in tech investing, valuation tends to get ignored or largely ignored." Betting on FAANG stocks PRSCX owns all the major FAANG names (Meta, Apple, Amazon and Alphabet), except for Netflix, and dominant chipmakers benefiting from AI such as Nvidia and Advanced Micro Devices , up 189% and 70%, respectively, this year. Other key holdings include Microsoft , Salesforce and German online retailer Zalando. Just two stocks combined Microsoft and Alphabet made up nearly a fifth of the fund's portfolio as of as of March 31. Both stocks have gained more than 38% this year as investors bet on the promise of AI and the pair battle to offer the best generative AI model. But the fund's favored Microsoft since 2008 and bought Alphabet last summer, long before their latest gains. Allen expects recent technology trends to continue boosting what he regards as high-quality names, and applies the same philosophy to a position in Amazon now the fund's fourth-largest holding. Allen stood by Microsoft even as a PC-fueled down cycle and uncertainty rocked the technology sector in 2022, driving down shares in the Xbox maker by about 29%. Allen opened his position in Alphabet last year, just as the slowing advertising cycle turned many investors away from the Google parent, dropping its multiple to the low teens. Allen viewed its solid fundamentals as unchanged. "It's kind of unusual to get a great business at a lower PE than it's likely ...growth rate, and that's why I felt really comfortable having a particularly large position then in the stock," he explained. The same idea cemented Allen's faith in Salesforce last year, even as shares cratered 48%, its business slowed and the co-CEO announced his departure. The stock proved one of Allen's biggest losers in 2022, but the portfolio manager expects significant upside as IT spending improves. Salesforce has rebounded more than 58% this year. "I looked at this company that I think is a top line grower, well into the double digits, with a ton of margin expansion, trading at 15 times free cash flow, and it just didn't make sense to me that a business this good would be this discounted," Allen said. Given his devotion to valuation, Allen has lately pulled back his exposure to some technology names that have rallied, significantly reducing stakes in Nvidia, Meta Platforms, Advanced Micro Devices and Amazon. Unusual plays and new additions Not every name in Allen's portfolio is widely bought on Wall Street. Despite a recent selloff in Zalando , Allen said shares look "really cheap" and the company appears well-situated to take market share with its vast item selection. The stock, one of Allen's top 10 as of March 31, is undervalued by at least half on the basis of its long-term cash flow projections, and could potentially triple within the next few years, he calculates, he said. Accenture , which this week forecast weaker-than-estimated revenue in the current quarter , remains a "premier" technology services company able to guide businesses as they look to implement AI. It was Allen's 7th largest position at the end of March. Recent additions to the fund include Mastercard , Apple and Texas Instruments . While Mastercard lags the stock performance of many technology behemoths, Allen believes it offers similar growth potential, and less cyclicality and fewer risks. A low-risk approach also extends to Texas Instruments. While the analog semiconductor name is ahead less than 2% this year, Allen said it offers a strong track record of driving shareholder value and returning capital through buybacks and dividends. TXN yields 3%. Lately, the T. Rowe Price fund has outperformed even when it's slumped. The fund tumbled more than 35% during last year's rout, but other tech funds lost an average of 37.4%, according to Morningstar. For Allen, every investment and every cycle marks another learning opportunity to perfect his craft. "It's really important to learn over time when things go well and especially when things don't go well," Allen said. "One of the things that I focus on a lot, and have for the 23 years I've been doing this, is thoughtfully evaluating what I can do to just get incrementally better while sticking to a process that I believe in."
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Bets on A.I. and innovation help this tech-focused T. Rowe Price ... - CNBC
AWS is investing $100 million in generative A.I. center in race to keep up with Microsoft and Google – CNBC
Amazon Web Services CEO Adam Selipsky speaks at the CERAWeek by S&P Global conference in Houston on March 7, 2023.
F. Carter Smith | Bloomberg | Getty Images
Amazon's cloud unit said Thursday that it's allocating $100 million for a center to help companies use generative artificial intelligence, the technology that's taken off in the months since OpenAI unleashed its ChatGPT chatbot on the public.
It's a small investment for a company with $64 billion in cash and half a trillion dollars a year in operating expenses. But the announcement shows that Amazon Web Services recognizes the significance of the current moment in generative AI and the importance of being in the conversation, alongside rivals Microsoft and Google.
"You ask yourself the question where are the different runners three steps into a 10K race?" AWS CEO Adam Selipsky said in an interview this week with CNBC. "Does it really matter? The point is, you're three steps in, and it's a 10K race."
As part of the latest announcement, Amazon said it will be adding some data scientists, engineers and solutions architects to the payroll. AWS said the center is already working with Highspot, Twilio, RyanAir and Lonely Planet. The company told CNBC that it's a "program" rather than a physical center.
Amazon, which beat Microsoft and Google to the business of renting out servers and data storage to companies and other organizations, enjoys a commanding lead in the cloud infrastructure market. However, those rivals have had splashier entrances into generative AI, even though Amazon has drawn broadly on AI for years to show shopping recommendations and operate its Alexa voice assistant.
Microsoft has been spending billions on a multilayered alliance with OpenAI, and Google is moving quickly to deploy AI tools it's built in-house for consumers and businesses.
Nor does Amazon have the first popular large language model that can enable a chatbot or a tool for summarizing documents.
Selipsky said he isn't concerned. He joined the company in 2005, a year before the launch of AWS' core services for computing and storage. Echoing Amazon founder and longtime CEO Jeff Bezos, Selipsky said the company has succeeded by listening to customers.
"Amazon has had many examples in its history where it said, we're going to focus on customers and have steadfast belief that we're going to work with customers, we're going to build what they want," Selipsky said. "And if people want to perceive us in a certain way, we're misunderstood, that's OK, as long as customers understand where we're going."
One challenge Amazon currently faces is in meeting demand for AI chips. The company chose to start building chips to supplement graphics processing units from Nvidia, the leader in the space. Both companies are racing to get more supply on the market.
"I think the whole world has a shortage in the short term of compute capacity for doing generative AI and machine learning in general right now," Selipsky said. People are impatient, and the situation will improve in the next few months, he added.
Selipsky is also reckoning with a slowdown in customer spending on cloud, as businesses prepare for ongoing economic uncertainty.
"A lot of customers are largely through their cost optimization, but there have been other customers who are still right in the middle of it," he said. "It's hard to predict exactly when that particular trend will be over. But we're still in the middle of it."
Still, the AI trend is real, he insists. For Amazon, that momentum applies to its Bedrock generative AI service and its Titan models as well as the new innovation center.
"AI is going to be this next wave of innovation in the cloud," he said. "It's going to be the next big thing that pushes even more customers to want to be in the cloud. Really, you need the cloud for generative AI."
Also, the way Selipsky sees it, AWS provides a measure of credibility in offering generative AI that eludes others in the space.
"I can't tell you how many Fortune 500 companies I've talked to who banned ChatGPT in the enterprise," Selipsky said. "Because at least the initial versions of it just didn't have that concept of enterprise security."
WATCH: Amazon lawsuit is test of what FTC considers 'dark patterns'
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AI watch: from Wimbledon to job losses in journalism – The Guardian
Technology
This week in artificial intelligence
Fri 23 Jun 2023 08.00 EDT
Artificial intelligence is either going to save humanity or finish it off, depending on who you speak to. Either way, every week there are new developments and breakthroughs. Here are just some of the AI stories that have emerged in recent days
The Wimbledon tennis tournament revealed it will be introducing AI-generated audio and text commentary in its online highlights this year. The All England Club has teamed up with the tech group IBM to provide automatically created voiceovers and captions for its footage. The move, which is separate to the BBCs coverage of the tournament, follows use of the cloned voice of a British athletics commentator, Hannah England, for online coverage of the European Athletics Championships. Generative AI refers to the creation of text and images from a human prompt think ChatGPT and Midjourney but voice is becoming a prominent development in this area as well.
Fears over the existential threat posed by AI have come to the fore in recent months, but the potential impact on jobs is never far behind. A US visual effects company was forced this week to state that the use of AI in the opening sequence of a Disney+ series, Marvels Secret Invasion, did not mean someones job had been displaced.
The film industry has been a locus for AI-related job concerns in recent months, which is understandable given that generative AI has obvious implications for workers and artists in fields such as film, TV and music. Fears over the use of AI in scriptwriting have been a factor in the US screenwriters strike, while the US arts and media union Sag-Aftra is demanding guardrails for replicating actors images and voices in productions.
Another example of how AI could end up affecting journalism was highlighted when Germanys Bild tabloid, the biggest-selling newspaper in Europe, announced a 100m (85m) cost-cutting programme that would lead to about 200 redundancies. It warned staff that it expected to make further editorial cuts owing to the opportunities of artificial intelligence. Bilds publisher, Axel Springer SE, said in an email to staff seen by the rival Frankfurter Allgemeine newspaper that it would unfortunately be parting ways with colleagues who have tasks that in the digital world are performed by AI and/or automated processes.
Advances in AI are exciting, but just as important to the spread of the technology is its productisation: how it gets turned from a promising tech to a real product. Take FabricGenie, from the Millshop Online, a curtain retailer. Enter your design preferences as text, image or sketch, and the company runs a simple AI image generator to spit out unique patterns that you can print on to personalised drapes. Its not going to win any awards for cutting-edge technology, but its the sort of thing that will be more and more common across society over the coming years.
On Thursday a US judge ordered two lawyers and their law firm to pay a $5,000 (4,000) fine after ChatGPT generated fake citations in a legal filing. A district judge in Manhattan ordered lawyers Steven Schwartz, Peter LoDuca and their law firm Levidow, Levidow & Oberman to pay the fine after fictitious legal research was used in an aviation injury claim. Schartz had admitted that ChatGPT, whose responses can appear very plausible, had invented six cases he referred to in a legal brief in a case against the airline Avianca. The legal work sector is a prime candidate for being transformed by generative AI, but this case raises questions over the extent to which AI can replace human work for now.
The UK government is taking warnings about artificial intelligence and safety seriously, before Rishi Sunak hosts a global summit on AI safety in the autumn. Last Sunday it announced that a tech entrepreneur who has warned about an unchecked race to achieve godlike AI will be the head of a new AI advisory body. Ian Hogarth wrote in April that a small number of companies were competing to achieve a breakthrough in computer superintelligence without knowing how to pursue their aim safely and with no oversight. Existential fears about AI include the emergence of a system that evades human intervention, or makes decisions that deviate from human moral values.
Hogarth will now have some influence in moderating the AI arms race as the chair of the UK governments AI Foundation Model taskforce (referring to the underlying technology for AI tools such as text or image generators). Writing in the Times after his appointment was announced, Hogarth said he had saw reasons for more optimism including further calls for action from AI experts and a 100m spending pledge for the UK taskforce, whose role will include identifying and tackling the safety challenges posed by the technology.
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AI watch: from Wimbledon to job losses in journalism - The Guardian
5 Stocks Well-Positioned to Reap Rewards of AI: Morgan Stanley – Business Insider
Since the launch of ChatGPT last November, artificial intelligence has been at the forefront of Wall Street's mind. Investors have poured money into the space, sending shares of AI-related firms such as Nvidia skyrocketing.
But while companies that directly deal with artificial intelligence have so far stolen the spotlight, investors would be wise to not overlook other potential beneficiaries.
For instance, another subset of technology firms that could capitalize on the rise of automation enabled by AI, especially in the near term, includes information technology services vendors.
"With most companies in the early innings of their digital transformations, on a 1-3 year view we see a demand tailwind as companies look to IT Services vendors to help them understand their data landscape and ways to leverage AI," wrote a team of Morgan Stanley analysts in a report from June 19.
They continued: "Therefore, irrespective of the pace of AI advancements and eventual scope for cost and complexity reductions, customers will continue to lean heavily on vendors who can provide informed advice and support."
The analysts noted that in the short term, these benefits are likely to be smaller in impact and limited to early adopters and service vendors that have robust in-house talent, financial resources, and existing customer relationships.
But over the long term, the potential implications of AI adoption are less clear, the analysts said.
"Given the IT industry is constantly changing, what is 'digital' today, will likely prove 'traditional' or 'legacy' in 10 years time, underpinning the view that IT Services vendors are built on change," they wrote. They added that generative artificial intelligence is more likely to revolutionize the world than previous "tech hype cycles" like the metaverse.
Although this may be true, the analysts also noted that information technology firms have traditionally been quick to adapt to and adjust for technological advancements. "While it remains early days and the impact on the total addressable market remains to be seen, we don't expect IT vendors to be disintermediated in the age of AI," the analysts explained.
In fact, it's more likely that AI will prove a long-term tailwind for IT firms by speeding up data services, and the industry as a whole should be able to successfully pivot with minimal disruptions, the team concluded.
Even within the information technology industry, it's clear that not all firms are created equally. The Morgan Stanley analysts currently favor companies that have the capacity to invest in AI at scale and offer services that are more likely to see increased short-term demand and less threatened by disruption, such as consulting.
Additionally, the analysts also recommend focusing on companies that offer higher value-add services, such as digital and cloud offerings, and have a well-documented history of agility when adapting to industry change as more attractive than their peers.
"Demand for engagement will continue to accrue in vendors more focused on consulting, and those who have deeper strategic partnerships with their customers or deeper industry understanding," they explained.
In the report, the analysts identified five information technology companies that are uniquely positioned to become key beneficiaries of rising artificial intelligence adoption. Those five stocks are listed below, along with each company's ticker, market capitalization, and respective analyst commentary.
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5 Stocks Well-Positioned to Reap Rewards of AI: Morgan Stanley - Business Insider
ChatGPT-maker OpenAI planning to launch marketplace for AI applications – Business Today
The company behind the famous platform ChatGPT is reportedly planning to launch a marketplace. This platform by OpenAI will mainly focus on use by enterprises. This marketplace would enable developers to sell their AI models built on top of OpenAI's own AI technology, according to a report by The Information.
The marketplace aims to cater to enterprise customers who often customize OpenAI's ChatGPT technology for specific use cases, such as fraud detection or market research. The models created by these developers could be made available to other businesses through OpenAI's proposed marketplace.
The report suggests the potential plans for the marketplace were revealed by OpenAI CEO Sam Altmanduring a meeting with developers in London. If realized, this marketplace could potentially compete with existing app stores operated by OpenAI's customers and technology partners, including Salesforce and Microsoft. Additionally, it could help OpenAI expand its customer base and make its technology more accessible to a wider audience.
Also read:Hed been misunderstood: Anand Mahindra and Sam Altman foster positive outlook on Indian innovation
The Information, which reported on these developments, also mentioned that two OpenAI customers, Aquant (a manufacturer software provider) and Khan Academy (an education app maker), may express interest in offering their AI models powered by ChatGPT on OpenAI's marketplace.
Since its launch in late 2022, ChatGPT has gained significant adoption among businesses looking to automate tasks and enhance operational efficiency. As companies race to leverage the capabilities of advanced large language models (LLMs), offering customers new tools based on AI software has become a competitive market.
Also read:BT Best B-School & HR Summit: Should writers be worried about ChatGPT?
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ChatGPT-maker OpenAI planning to launch marketplace for AI applications - Business Today
Artificial Intelligence in Asset Management Market to grow by USD 10,373.18 million from 2022 to 2027, Growing adoption of cloud-based artificial…
NEW YORK, June 26, 2023 /PRNewswire/ -- According toTechnavio, theartificial intelligence in asset management market size is estimated to grow by USD 10,373.18 millionfrom 2022 to 2027. The market is estimated to grow at a CAGRof 37.88%during the forecast. Download a Sample Report now!
Technavio has announced its latest market research report titled Global Artificial Intelligence in Asset Management Market
Information Services Market Insights -
Vendors: 15+, IncludingAmazon.com Inc., AXOVISION GmbH, BlackRock Inc., Deloitte Touche Tohmatsu Ltd., Genpact Ltd., Infosys Ltd., International Business Machines Corp., Lexalytics Inc., Microsoft Corp., New Narrative Ltd., Salesforce Inc., and The Charles Schwab Corp. among others
Coverage:Parent market analysis; key drivers, major trends, and challenges; customer and vendor landscape; vendor product insights and recent developments; key vendors; and market positioning of vendors
Segments:Deployment (On-premises and Cloud), Industry Application (BFSI, retail and e-commerce, healthcare, energy and utilities, and others), and Geography (North America, Europe, APAC, Middle East and Africa, and South America)
To understand more about the information services market, requesta sample report
Artificial Intelligence in asset management market - Vendor Insights
The growing competition in the market is compelling vendors to adopt various growth strategies such as promotional activities and spending on advertisements to improve the visibility of their services. Technavio report analyzes the market's competitive landscape and offers information on several market vendors includingAmazon.com Inc., AXOVISION GmbH, BlackRock Inc., Deloitte Touche Tohmatsu Ltd., Genpact Ltd., Infosys Ltd., International Business Machines Corp., Lexalytics Inc., Microsoft Corp., New Narrative Ltd., Salesforce Inc., and The Charles Schwab Corp.
Artificial Intelligence In Asset Management Market Market Dynamics
Major Drivers -
The rapid adoption of artificial intelligence in asset management and the growing importance of asset tracking is notably driving the market growth. Artificial intelligence (AI) is transforming the asset management industry by enabling asset managers to make faster, more informed investment decisions. AI algorithms can analyze large amounts of data in real-time to identify trends and patterns that humans might miss. This allows asset managers to track asset performance, optimize asset allocation, and reduce risk. AI is also changing the way assets are tracked and managed. With the Internet of Things (IoT), assets can be equipped with sensors and other devices that collect data about their condition, location, and usage. This data can be used to provide real-time insights into asset health, availability, and utilization. This enables asset managers to optimize asset utilization, minimize downtime, reduce costs, and maximize revenue. Therefore, such advancements in asset management are anticipated to drive AI in asset management market growth during the forecast period.
Story continues
Significant Trends -
The growing adoption of cloud-based artificial intelligence services in asset management is an emerging trend shaping theArtificial Intelligence in Asset Management market growth.This is due to the cost-efficiency, scalability, and customization capabilities of cloud-based AI services. Cloud-based AI services allow asset managers to process large amounts of data, identify patterns and trends, and make decisions based on real-time information. This helps wealth managers quickly analyze economic data, market trends, and other variables that affect investments. AI models also help optimize portfolios by identifying the most profitable investments. Another advantage of cloud-based AI services is that they can be customized to meet the needs of different asset managers. The increased availability of data is one of the factors driving the adoption of cloud-based AI in asset management. Asset managers have large amounts of data at their disposal, including economic indicators, financial reports, and other relevant sources of information. Cloud-based AI services quickly process this data and provide wealth managers with real-time insights that can be used in making investment decisions. As a result of these factors, the global AI in the asset management market is expected to grow significantly in the coming years. Asset managers have large amounts of data at their disposal, including economic indicators, financial reports, and other relevant sources of information. Cloud-based artificial intelligence services quickly process this data and provide wealth managers with real-time insights that can be used in making investment decisions. Therefore, these factors are expected to drive the growth of AI in the asset management market during the forecast period.
KEY challenges -
The rising number of data privacy and cybersecurity issues is a major challenge impedingthe growth of global artificial intelligence (AI) in the asset management market.While artificial intelligence technology delivers numerous advantages for asset management firms, along with major privacy and cybersecurity concerns.However, wealth management companies majorly depend on big data sets to make decisions and such data sets.Another significant problem is the use of external data sources, which can lead to data access and ownership issues. When artificial intelligence systems rely on such data sources, it can be difficult to verify data processing and determine information ownership. Additionally, asset management firms must guarantee that security systems are in place to safeguard against cyberattacks and data breaches. As artificial intelligence systems are blended into business operations, they become more vulnerable and need specific cybersecurity and privacy safeguards. Furthermore, the use of artificial intelligence may automate certain duties that were formerly functioned by humans. While this improves productivity and efficiency and evenleads to job losses. Ultimately, the problem of regulatory compliance remains a significant challenge. Different laws and regulations in various jurisdictions governing data protection, cybersecurity, and the use of artificial intelligence make it challenging for wealth management firms to guide the compliance landscape. Therefore, a growing number of cyber-attacks and data breaches may hinder AI in asset management market growth during the forecast period.
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The artificial intelligence in asset management market report provides critical information and factual data, with a qualitative and quantitative study of the market based on market drivers and limitations as well as future prospects.
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What are the key data covered in this Artificial Intelligence In Asset Management Market report?
CAGR of the market during the forecast period
Detailed information on factors that will drive the growth of artificial intelligence in asset management market between 2023 and 2027
Precise estimation of the size of the artificial intelligence in asset management market size and its contribution to the market in focus on the parent market
Accurate predictions about upcoming trends and changes in consumer behavior
Growth of artificialintelligence in asset management marketindustry across North America, Europe, APAC, Middle East and Africa, and South America
A thorough analysis of the market's competitive landscape and detailed information about vendors
Comprehensive analysis of factors that will challenge the growth of artificial intelligence in asset management market vendors
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Artificial Intelligence in Asset Management Market Scope
Report Coverage
Details
Base year
2022
Historic period
2017-2021
Forecast period
2023-2027
Growth momentum & CAGR
Accelerate at a CAGR of 37.88%
Market growth 2023-2027
USD 10,373.18 million
Market structure
Concentrated
YoY growth 2022-2023(%)
35.12
Regional analysis
North America, Europe, APAC, Middle East and Africa, and South America
Performing market contribution
North America at 49%
Key countries
US, China, Germany, UK, and France
Competitive landscape
Leading Vendors, Market Positioning of Vendors, Competitive Strategies, and Industry Risks
Key companies profiled
Amazon.com Inc., AXOVISION GmbH, BlackRock Inc., Deloitte Touche Tohmatsu Ltd., Genpact Ltd., Infosys Ltd., International Business Machines Corp., Lexalytics Inc., Microsoft Corp., New Narrative Ltd., Salesforce Inc., and The Charles Schwab Corp.
Market dynamics
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for the forecast period
Customization purview
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized.
Table of contents
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Application
7 Market Segmentation by Component
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Trends
11 Vendor Landscape
12 Vendor Analysis
13 Appendix
About UsTechnavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provide actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.
ContactTechnavio ResearchJesse MaidaMedia & Marketing ExecutiveUS: +1 844 364 1100UK: +44 203 893 3200Email: media@technavio.comWebsite: http://www.technavio.com
Global Artificial Intelligence in Asset Management Market
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Translating Japanese, finding rap rhymes: How these young Toronto-area workers are using AI – Toronto Star
Its hard to believe that ChatGPT has only been around since November. Half a year later, OpenAIs robot has taken the world by storm.
The tech startup upped the ante this May, when it released its latest artificial intelligence model called GPT-4, which, with the right prompts (and a $20 monthly subscription), can write songs, code software and process images.
Now, young Canadians across various industries are using the software to brainstorm campaigns, elevate their writing and scour the internet for resources.
The Star spoke with five young people working in Toronto and the GTA about how and why theyre using the software and what changes it has brought to their workdays. Several of them said they see AI as an imperfect tool that requires a skilled and thoughtful person to work well. Some also said they think its important to learn how to use the robot now so that they can hold onto their competitive edge in the workforce.
Anusha Sheikh, 23, says she and her coworkers began exploring ChatGPT when clients started asking how the marketing consultancy would be implementing the cool things that AI can do. As a result, the team spent a few days studying and testing out ChatGPT, and creating guidelines for how and how not to use it.
I look at ChatGPT as my minion, she said.
It can be helpful, but its not entirely trustworthy, she explained. Thats why Sheikh said she only gives ChatGPT mundane tasks, like mixing up her vocabulary or making an email sound more professional. When shes overwhelmed and neck deep in data, she also might feed it a few different ideas that will help her better articulate the theme of her points, she says. She would also use it as a starting point, for example, asking ChatGPT for questions that could be used in a survey about customers experience with a product.
Click to expand
However, Sheikh highlighted that she takes privacy precautions and never feeds private information about clients or primary market research, which could potentially be stored and shared elsewhere. She recounted an experience using the software for research, in which a request for a facts source prompted the bot to disclose that the information it sent her was fabricated.
It literally just wrote back to me saying, I cant give you the source for this fact because its fake, she said.
Jaylen Banton, also known on stage as Blue Rivers, is a Brampton rapper who has used ChatGPT "a couple of times" for rhymes. (Kian Gannon)
Jaylen Banton, known on stage as Blue Rivers, said hes only used ChatGPT a couple of times to help him through a writers block.
The Brampton-based rapper recalled his experience writing a song about having fun with his friends, and trying to rhyme with Wu Tang Clan. At first, the words and phrases ChatGPT suggested werent cutting it, so the 25-year-old refined his input to clarify he wanted something with three syllables that also referred to a group of people.
He finally went with the suggested cool jazz band.
Those are things that I would usually be able to do, but I just couldnt that day, so I asked the robot for help, he said.
The more concrete ideas that I had, the more concrete help I can get from ChatGPT, he explained.
Nev Golubovic, a business development representative at a Toronto-based tech sales company, has only been using ChatGPT for about a month and a half since a friend showed her the ins and outs.
While she originally thought it would be the end all, be all, she quickly realized its a tool that requires her skills to work well.
At work, Golubovic uses AI to edit emails although she warns that ChatGPT can sometimes produce a Victorian era tone that needs its own editing and to find research sources. Additionally, she uses the software to find out more about her clients, asking questions like What does the vice president of construction at a highrise company in Vancouver care about?
Given Ive been in my role for over a year now, Im sure it would have been much more useful for me in the very beginning, she said. Now that Im really good at my job and I know my resources and whatnot, it doesnt do that much for me.
(Using ChatGPT is) almost like youre co-creating with someone and youre bouncing ideas off someone, she said.
Huy Tran is the marketing lead for a fine dining restaurant group. He has been implementing the use of AI across his team of eight people. (Supplied)
Huy Tran is the marketing lead for Aburi Restaurants, a group offering fine dining Japanese concepts in various Toronto and Vancouver properties. Although the Millennial said he and the CEO were initially reserved about adopting ChatGPT, Huy spent time learning about the tool and researching best practices, and ultimately rolled it out to his team of eight.
Ive been hearing great feedback in terms of reducing resources and time and effort into doing certain tasks, he said.
The team uses ChatGPT and Grammarly for copywriting on social media, blog posts, basic nondisclosure agreements and menu text.
We use various traditional Japanese ingredients that sometimes are not very common to non-Japanese folks, he said, adding that they have used the software to translate and explain ingredients from Japanese to English.
When it comes to precautions, the team never enters private information into text-based AI. They have also used Adobe Firefly an AI art generator which is meant to be for inspiration, but not meant to be for application. The software is still not legal to use for commercial purposes, he explained.
Working in marketing in todays economy, Zoe S-G said they feel the need to adapt or die. Since April, the Toronto brand manager and creative director has been using ChatGPT to help guide their market research, copywrite and generate ideas.
For example, in their role, the 24-year-old plans social media posts. They could tell ChatGPT about their company and what they would like to focus on, and then ask for 30 post ideas for the month. They also may ask broad questions about marketing research and use the answers as a starting off point.
With marketing, automation has always been a really big source of innovation, so ChatGPT and AI was like the next step, they said about the decision to adopt it.
However, S-G said theres a harmful misconception that ChatGPT can do and solve way more than it actually can.
It cant replace fields where people work on the needs of other people, they said.
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