
Artificial Intelligence Explainer: The Martech Glossary
(
Artificial Intelligence
) is the simulation of human intelligence processes by computer systems. In
MarTech
, AI is used for personalisation,
predictive analytics
, automation and more.
AI captured public imagination in recent times, when
ChatGPT
developed by
OpenAI
was launched as a "research preview" on November 30, 2022. Within a week, the world was talking about the development.
However, the origins of Artificial Intelligence (AI) can be traced back to the mid-20th century, with its roots in mathematics, philosophy and computer science. While the idea of creating intelligent machines has been contemplated for centuries, the modern field of AI as an academic discipline began in the 1950s.
The formal beginning of AI as a field of research is widely considered to be the Dartmouth Workshop in 1956. This summer conference, organised by John McCarthy, brought together leading researchers to discuss the possibility of creating "thinking machines." It was at this workshop that McCarthy coined the term "artificial intelligence."
Before this pivotal event, several key figures laid the groundwork for the future of AI.
Alan Turing, often called the "father of computer science," explored the concept of machine intelligence in his 1950 paper, "Computing Machinery and Intelligence". He proposed the Turing Test, a method for determining if a machine could exhibit intelligent behavior indistinguishable from that of a human.
In 1943, Warren McCulloch and Walter Pitts published a paper that provided a mathematical description of how neurons in the brain might work, which was a crucial step toward the development of artificial neural networks.
Arthur Samuel, a computer scientist at IBM, created a checkers program in the early 1950s that could learn from its own experience and improve its gameplay, a foundational example of machine learning.
Following the Dartmouth Workshop, the field of AI experienced periods of rapid growth and setbacks, often referred to as "AI winters".
The early years saw a great deal of optimism and progress. Researchers like Marvin Minsky, Allen Newell, and Herbert A Simon developed some of the first AI programs, including the Logic Theorist, which could solve mathematical theorems.
The decade of the 1970s marked the first "AI winter," as funding and interest waned due to the failure of AI to deliver on its ambitious promises.
In the 1980s, a resurgence of interest occurred with the rise of "expert systems," which were designed to mimic the decision-making of human experts in specific domains.
From the 1990s, the emergence of machine learning approaches and the first major AI victories in games, such as IBM's Deep Blue defeating world chess champion Garry Kasparov in 1997 were highlights in the progress of AI.
The current "AI boom" has been fueled by the availability of vast amounts of data, increased computational power, and the development of
deep learning techniques
, particularly with the introduction of the transformer architecture in 2017, which has been instrumental in the creation of large language models like GPT.
The public release of ChatGPT in late 2022 was a landmark moment, as it brought the power of this technology to a wide audience and sparked a massive surge of interest and investment in
Generative AI
.
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Time of India
13 minutes ago
- Time of India
Alexa got an AI brain transplant: How smart is it now
Tired of too many ads? Remove Ads Tired of too many ads? Remove Ads Tired of too many ads? Remove Ads For the last few years, I've been waiting for Alexa 's AI glow-up.I've been a loyal user of Alexa, the voice assistant that powers Amazon 's home devices and smart speakers, for more than a decade. I have five Alexa-enabled speakers scattered throughout my house, and while I don't use them for anything complicated -- playing music, setting timers and getting the weather forecast are basically it -- they're good at what they since 2023, when ChatGPT added an AI voice mode that could answer questions in a fluid, conversational way, it has been obvious that Alexa would need a brain transplant -- a new AI system built around the same large language models, or LLMs, that power ChatGPT and other products. LLM-based systems are smarter and more versatile than older systems. They can handle more complex requests, making them an obvious pick for a next-generation voice agrees. For the last few years, the company has been working feverishly to upgrade the AI inside Alexa. It has been a slog. Replacing the AI technology inside a voice assistant isn't as easy as swapping in a new model, and the Alexa remodel was reportedly delayed by internal struggles and technical challenges along the way. LLMs also aren't a perfect match for this kind of product, which not only needs to work with tons of preexisting services and millions of Alexa-enabled devices but also needs to reliably perform basic finally, the new Alexa -- known as Alexa+ -- is here. It's a big, ambitious remodel that is trying to marry the conversational skills of generative AI chatbots with the daily tasks that the old Alexa did which has been available to testers through an early-access program for a few months, is now being rolled out more widely. I got it recently after I bought a compatible device (the Echo Show 8, which has an 8-inch screen) and enrolled in the upgraded version. (Prime members will get Alexa+ at no cost, while non-Prime members will have to pay $19.99 per month.)The New York Times recently announced a licensing deal with Amazon, which will allow Amazon to use Times content in its AI systems, including Alexa+. The Times is also suing OpenAI, the maker of ChatGPT, and Microsoft for alleged copyright violations related to the training of AI systems.I have good news and bad news for my fellow good news is that the new Alexa+ is, in fact, more fun to talk to than the old one, with more realistic synthetic voices and a more humanlike cadence. (There are eight voices to choose from; I used the default setting, an upbeat female voice.)And I liked some of Alexa+'s new capabilities, such as booking a table at a restaurant and generating long stories and reading them to my new Alexa is also better at handling multistep requests. "Set three kitchen timers for 15, 25 and 45 minutes" and "write a one-day itinerary for a trip to San Diego and send it to my email" were two prompts that worked for Alexa+ doesn't require you to say its wake word every time you talk to it, so you can go back and forth or ask it follow-up questions, which is a nice bad news is that despite its new capabilities, Alexa+ is too buggy and unreliable for me to recommend. In my testing, it not only lagged behind ChatGPT's voice mode and other AI voice assistants I've tried but also was noticeably worse than the original Alexa at some basic I asked Alexa+ to cancel an alarm the other morning -- a request I had made to the old Alexa hundreds of times with no issues -- it simply ignored I emailed a research paper to alexa@ in order to hear Alexa+ summarize it while I washed the dishes, I got an error message saying the document couldn't be also hallucinated some facts and made some inexplicable errors. When I asked it to look up Wirecutter 's recommended box grater and add it to my Amazon cart, it responded that "according to Wirecutter, the best box grater is the OXO Good Grips Box Grater." Wirecutter's actual box grater pick is the Cuisipro 4-Sided Box Grater. Luckily, I caught the mistake before ordering. When I asked Alexa+ to walk me through installing a new AI model on my laptop, it got tripped up and started repeating, "Oh, no, my wires got crossed."And I didn't have access to some of the new Alexa+ features Amazon advertised, such as a "routine" feature that triggers several different actions when a user enters a room. (I wanted to have Alexa+ greet me in the mornings with a motivational speech and a high-volume rendition of "Eye of the Tiger," but the presence-sensing feature hasn't been turned on yet, according to an Amazon spokesperson.)Daniel Rausch , the Amazon vice president who oversees Alexa and Echo, told me in a recent podcast interview that many of these flaws would be fixed soon as Alexa+ rolled out more widely and more of its features came online."We've got some edges to sand," he said the biggest challenge in building generative AI models into Alexa was that they were fundamentally different types of old Alexa, he said, was built on a complicated web of rule-based, deterministic algorithms. Setting timers, playing songs on Spotify, turning off the lamp in your living room -- all of these features required calling up different tools and connecting with different interfaces, and they all had to be programmed one by generative AI to Alexa forced Amazon to rebuild many of these processes, Rausch said. Large language models, he said, are "stochastic," meaning they operate on probabilities rather than a strict set of rules. That made Alexa more creative but less also made the voice assistant slow. Rausch recalled an early internal demo in which Alexa+ took more than 30 seconds to play a song -- an "excruciating" delay, he said, that led the team to rethink its approach."These models are slow to respond when they're following a deep set of instructions," he said. "We're asking them to do something quite hard."Another challenge to overcome, Rausch said, was generative AI's wordiness. Initially, when engineers hooked Alexa up to large language models, the system would sometimes produce long, verbose answers or introduce needless complexity. Alexa+ might respond to a user's request for a 10-minute kitchen timer with a 500-word essay about the history of kitchen solution, Rausch said, was to spend several years combining more than 70 AI models -- some Amazon's proprietary models and some from outside providers, like Anthropic's Claude -- into a single, voice-based interface, with an orchestration system that routes a user's request to the model that is best suited to handle it."The magic, when it is working really well, is to get those new ways of speaking to Alexa to interface with those predictable outcomes or behaviors," he are other barriers, too. One of them, Rausch said, is that many longtime users have learned how to "speak Alexa," phrasing their daily requests in familiar commands that they know the system will understand."We all sort of came up with our way of setting a timer to get the pasta done on time," he Alexa+ processes language in a more fluid way. Users can talk to it as they would talk to a human -- no robot pidgin required -- and that may necessitate some retraining.I assume that many of the flaws will be ironed out and that most users will acclimate to the new way of speaking to Alexa+. I'm also inclined to cut Amazon some slack, since building LLM-based technology into a reliable voice assistant seems like a thorny technical problem, and it's not like anyone else has solved it. ( Apple , which has been struggling to give Siri an AI upgrade for years, certainly hasn't.)I also don't think the limitations of Alexa+ suggest that generative AI models are inherently unreliable or that they'll never work as personal voice assistants. Ultimately, I think it's just really hard to combine generative AI with older, legacy systems -- a lesson many companies, both inside and outside tech, are learning the hard way right now -- and it's going to take some time to work out all the now, I'm going to downgrade my devices to the older, less intelligent version of Alexa and leave the beta testing to others. With AI, as with humans, sometimes raw intelligence matters less than how you use it.


Economic Times
13 minutes ago
- Economic Times
Are you in a mid-career to senior job? Don't fear AI - you could have this important advantage
ET Online Have you ever sat in a meeting where someone half your age casually mentions "prompting ChatGPT" or "running this through AI", and felt a familiar knot in your stomach? You're not alone. There's a growing narrative that artificial intelligence (AI) is inherently ageist, that older workers will be disproportionately hit by job displacement and are more reluctant to adopt AI tools. But such assumptions - especially that youth is a built-in advantage when it comes to AI - might not actually hold. While ageism in hiring is a real concern, if you have decades of work experience, your skills, knowledge and judgement could be exactly what's needed to harness AI's power - without falling into its traps. What does the research say? The research on who benefits most from AI at work is surprisingly murky, partly because it's still early days for systematic studies on AI and work. Some research suggests lower-skilled workers might have more to gain than high-skilled workers on certain straightforward tasks. The picture becomes much less clear under real-world conditions, especially for complex work that relies heavily on judgement and experience. Through our Skills Horizon research project, where we've been talking to Australian and global senior leaders across different industries, we're hearing a more nuanced story. Many older workers do experience AI as deeply unsettling. As one US-based CEO of a large multinational corporation told us: "AI can be a form of existential challenge, not only to what you're doing, but how you view yourself." But leaders are also observing an important and unexpected distinction: experienced workers are often much better at judging the quality of AI outputs. This might become one of the most important skills, given that AI occasionally hallucinates or gets things wrong. The CEO of a South American creative agency put it bluntly: "Senior colleagues are using multiple AIs. If they don't have the right solution, they re-prompt, iterate, but the juniors are satisfied with the first answer, they copy, paste and think they're finished. They don't yet know what they are looking for, and the danger is that they will not learn what to look for if they keep working that way." Experience as an AI advantage Experienced workers have a crucial advantage when it comes to prompting AI: they understand context and usually know how to express it clearly. While a junior advertising creative might ask an AI to "Write copy for a sustainability campaign", a seasoned account director knows to specify "Write conversational social media copy for a sustainable fashion brand targeting eco-conscious millennials, emphasising our client's zero-waste manufacturing process and keeping the tone authentic but not preachy". This skill mirrors what experienced professionals do when briefing junior colleagues or freelancers: providing detailed instructions, accounting for audience, objectives, and constraints. It's a competency developed through years of managing teams and projects. Younger workers, despite their comfort with technology, may actually be at a disadvantage here. There's a crucial difference between using technology frequently and using it well. Many young people may become too accustomed to AI assistance. A survey of US teens this year found 72 per cent had used an AI companion app. Some children and teens are turning to chatbots for everyday decisions. Without the professional experience to recognise when something doesn't quite fit, younger workers risk accepting AI responses that feel right - effectively "vibing" their work - rather than developing the analytical skills to evaluate AI usefulness. So what can you do? First, everyone benefits from learning more about AI. In our time educating everyone from students to senior leaders and CEOs, we find that misunderstandings about how AI works have little to do with age. A good place to start is reading up on what AI is and what it can do for you: What is AI? Where does AI come from? How does AI learn? What can AI do? What makes a good AI prompt? If you're not even sure which AI platform to try, we would recommend testing the most prominent ones, OpenAI's ChatGPT, Anthropic's Claude, and Google's Gemini. If you're an experienced worker feeling threatened by AI, lean into your strengths. Your decades of experience with delegation, context-setting, and critical evaluation are exactly what AI tools need. Start small. Pick one regular work task and experiment with AI assistance, using your judgement to evaluate and refine outputs. Practice prompting like you're briefing a junior colleague: be specific about context, constraints, and desired outcomes, and repeat the process as needed. Most importantly, don't feel threatened. In a workplace increasingly filled with AI-generated content, your ability to spot what doesn't quite fit, and to know what questions to ask, has never been more valuable. Elevate your knowledge and leadership skills at a cost cheaper than your daily tea. Can Coforge's ambition to lead the IT Industry become a reality? How Mukesh Ambani's risky bet has now become Reliance's superpower Berlin to Bharuch: The Borosil journey after the China hit in Europe As RBI retains GDP forecast, 4 factors that will test the strength of Indian economy In a flat market, are REITs the sweet spot between growth and safety? These large- and mid-cap stocks may give more than 25% return in 1 year, according to analysts Buy, Sell or Hold: Avendus trims target on Titan Company; Motila Oswal maintains buy on Jindal Stainless Stock picks of the week: 5 stocks with consistent score improvement and return potential of more than 23% in 1 year


Time of India
13 minutes ago
- Time of India
Are you in a mid-career to senior job? Don't fear AI
Academy Empower your mind, elevate your skills Have you ever sat in a meeting where someone half your age casually mentions "prompting ChatGPT" or "running this through AI", and felt a familiar knot in your stomach? You're not a growing narrative that artificial intelligence (AI) is inherently ageist, that older workers will be disproportionately hit by job displacement and are more reluctant to adopt AI such assumptions - especially that youth is a built-in advantage when it comes to AI - might not actually ageism in hiring is a real concern, if you have decades of work experience, your skills, knowledge and judgement could be exactly what's needed to harness AI's power - without falling into its does the research say?The research on who benefits most from AI at work is surprisingly murky, partly because it's still early days for systematic studies on AI and research suggests lower-skilled workers might have more to gain than high-skilled workers on certain straightforward tasks. The picture becomes much less clear under real-world conditions, especially for complex work that relies heavily on judgement and our Skills Horizon research project, where we've been talking to Australian and global senior leaders across different industries, we're hearing a more nuanced older workers do experience AI as deeply unsettling. As one US-based CEO of a large multinational corporation told us: "AI can be a form of existential challenge, not only to what you're doing, but how you view yourself."But leaders are also observing an important and unexpected distinction: experienced workers are often much better at judging the quality of AI outputs. This might become one of the most important skills, given that AI occasionally hallucinates or gets things CEO of a South American creative agency put it bluntly: "Senior colleagues are using multiple AIs. If they don't have the right solution, they re-prompt, iterate, but the juniors are satisfied with the first answer, they copy, paste and think they're finished. They don't yet know what they are looking for, and the danger is that they will not learn what to look for if they keep working that way."Experienced workers have a crucial advantage when it comes to prompting AI: they understand context and usually know how to express it a junior advertising creative might ask an AI to "Write copy for a sustainability campaign", a seasoned account director knows to specify "Write conversational social media copy for a sustainable fashion brand targeting eco-conscious millennials, emphasising our client's zero-waste manufacturing process and keeping the tone authentic but not preachy".This skill mirrors what experienced professionals do when briefing junior colleagues or freelancers: providing detailed instructions, accounting for audience, objectives, and constraints. It's a competency developed through years of managing teams and workers, despite their comfort with technology, may actually be at a disadvantage here. There's a crucial difference between using technology frequently and using it young people may become too accustomed to AI assistance. A survey of US teens this year found 72 per cent had used an AI companion app. Some children and teens are turning to chatbots for everyday the professional experience to recognise when something doesn't quite fit, younger workers risk accepting AI responses that feel right - effectively "vibing" their work - rather than developing the analytical skills to evaluate AI everyone benefits from learning more about AI. In our time educating everyone from students to senior leaders and CEOs, we find that misunderstandings about how AI works have little to do with age.A good place to start is reading up on what AI is and what it can do for you:What is AI? Where does AI come from? How does AI learn? What can AI do? What makes a good AI prompt?If you're not even sure which AI platform to try, we would recommend testing the most prominent ones, OpenAI's ChatGPT, Anthropic's Claude, and Google's you're an experienced worker feeling threatened by AI, lean into your strengths. Your decades of experience with delegation, context-setting, and critical evaluation are exactly what AI tools small. Pick one regular work task and experiment with AI assistance, using your judgement to evaluate and refine outputs. Practice prompting like you're briefing a junior colleague: be specific about context, constraints, and desired outcomes, and repeat the process as importantly, don't feel threatened. In a workplace increasingly filled with AI-generated content, your ability to spot what doesn't quite fit, and to know what questions to ask, has never been more valuable.