Summarize this content to 2000 words in 6 paragraphs in Arabic Amazon is gearing up to relaunch its Alexa voice-powered digital assistant as an artificial intelligence \u201cagent\u201d that can complete practical tasks, as the tech group races to resolve the challenges that have dogged the system\u2019s AI overhaul.The $2.4tn company has for the past two years sought to redesign Alexa, its conversational system embedded within 500mn consumer devices worldwide, so the software\u2019s \u201cbrain\u201d is transplanted with generative AI.\u00a0Rohit Prasad, who leads the artificial general intelligence (AGI) team at Amazon, told the Financial Times the voice assistant still needed to surmount several technical hurdles before the rollout.This includes solving the problem of \u201challucinations\u201d or fabricated answers, its response speed or \u201clatency\u201d, and reliability. \u201cHallucinations have to be close to zero,\u201d said Prasad. \u201cIt\u2019s still an open problem in the industry, but we are working extremely hard on it.\u201d\u00a0The vision of Amazon\u2019s leaders is to transform Alexa, which is currently still used for a narrow set of simple tasks such as playing music and setting alarms, to an \u201cagentic\u201d product that acts as a personalised concierge. This could include anything from suggesting restaurants to configuring the lights in the bedroom based on a person\u2019s sleep cycles. Alexa\u2019s redesign has been in train since the launch of OpenAI\u2019s ChatGPT, backed by Microsoft, in late 2022. While Microsoft, Google, Meta and others have quickly embedded generative AI into their computing platforms and enhanced their software services, critics have questioned whether Amazon can resolve its technical and organisational struggles in time to compete with its rivals. According to multiple staffers who have worked on Amazon\u2019s voice assistant teams in recent years, its effort has been beset with complications and follows years of AI research and development. Several former workers said the long wait for a rollout was largely due to the unexpected difficulties involved in switching and combining the simpler, predefined algorithms Alexa was built on, with more powerful but unpredictable large language models.\u00a0In response, Amazon said it was \u201cworking hard to enable even more proactive and capable assistance\u201d of its voice assistant. It added that a technical implementation of this scale, into a live service and suite of devices used by customers around the world, was unprecedented, and not as simple as overlaying a LLM on to the Alexa service.Prasad, the former chief architect of Alexa, said last month\u2019s release of the company\u2019s in-house Amazon Nova models \u2014 led by his AGI team \u2014 was in part motivated by the specific needs for optimum speed, cost and reliability, in order to help AI applications such as Alexa \u201cget to that last mile, which is really hard\u201d.\u00a0To operate as an agent, Alexa\u2019s \u201cbrain\u201d has to be able to call hundreds of third-party software and services, Prasad said. \u201cSometimes we underestimate how many services are integrated into Alexa, and it\u2019s a massive number. These applications get billions of requests a week, so when you\u2019re trying to make reliable actions happen at speed\u2009.\u2009.\u2009.\u2009you have to be able to do it in a very cost-effective way,\u201d he added.\u00a0The complexity comes from Alexa users expecting quick responses as well as extremely high levels of accuracy. Such qualities are at odds with the inherent probabilistic nature of today\u2019s generative AI, a statistical software that predicts words based on speech and language patterns.Some former staff also point to struggles to preserve the assistant\u2019s original attributes, including its consistency and functionality, while imbuing it with new generative features such as creativity and free-flowing dialogue.\u00a0Because of the more personalised, chatty nature of LLMs, the company also plans to hire experts to shape the AI\u2019s personality, voice and diction so it remains familiar to Alexa users, according to one person familiar with the matter.One former senior member of the Alexa team said while LLMs were very sophisticated, they come with risks, such as producing answers that are \u201ccompletely invented some of the time\u201d.\u00a0\u201cAt the scale that Amazon operates, that could happen large numbers of times per day,\u201d they said, damaging its brand and reputation.In June, Mihail Eric, a former machine learning scientist at Alexa and founding member of its \u201cconversational modelling team\u201d, said publicly that Amazon had \u201cdropped the ball\u201d on becoming \u201cthe unequivocal market leader in conversational AI\u201d with Alexa. Eric said despite having strong scientific talent and \u201chuge\u201d financial resources, the company had been \u201criddled with technical and bureaucratic problems\u201d, suggesting \u201cdata was poorly annotated\u201d and \u201cdocumentation was either non-existent or stale\u201d.\u00a0According to two former employees working on Alexa-related AI, the historic technology underpinning the voice assistant had been inflexible and difficult to change quickly, weighed down by a clunky and disorganised code base and an engineering team \u201cspread too thin\u201d.The original Alexa software, built on top of technology acquired from British start-up Evi in 2012, was a question-answering machine that worked by searching within a defined universe of facts to find the right response, such as the day\u2019s weather or a specific song in your music library.The new Alexa uses a bouquet of different AI models to recognise and translate voice queries and generate responses, as well as to identify policy violations, such as picking up inappropriate responses and hallucinations. Building software to translate between the legacy systems and the new AI models has been a major obstacle in the Alexa-LLM integration.The models include Amazon\u2019s own in-house software, including the latest Nova models, as well as Claude, the AI model from start-up Anthropic, in which Amazon has invested $8bn over the course of the past 18 months.\u00a0\u201c[T]he most challenging thing about AI agents is making sure they\u2019re safe, reliable and predictable,\u201d Anthropic\u2019s chief executive Dario Amodei told the FT last year. Agent-like AI software needs to get to the point \u201cwhere\u2009.\u2009.\u2009.\u2009people can actually have trust in the system\u201d, he added. \u201cOnce we get to that point, then we\u2019ll release these systems.\u201dOne current employee said more steps were still needed, such as overlaying child safety filters and testing custom integrations with Alexa such as smart lights and the Ring doorbell.\u201cThe reliability is the issue \u2014 getting it to be working close to 100 per cent of the time,\u201d the employee added. \u201cThat\u2019s why you see us\u2009.\u2009.\u2009.\u2009or Apple or Google shipping slowly and incrementally.\u201d\u00a0Numerous third parties developing \u201cskills\u201d or features for Alexa said they were unsure when the new generative AI-enabled device would be rolled out and how to create new functions for it.\u201cWe\u2019re waiting for the details and understanding,\u201d said Thomas Lindgren, co-founder of Swedish content developer Wanderword. \u201cWhen we started working with them they were a lot more open\u2009.\u2009.\u2009.\u2009then with time, they\u2019ve changed.\u201dAnother partner said after an initial period of \u201cpressure\u201d that was put on developers by Amazon to start getting ready for the next generation of Alexa, things had gone quiet.\u00a0An enduring challenge for Amazon\u2019s Alexa team \u2014 which was hit by major lay-offs in 2023 \u2014 is how to make money. Figuring out how to make the assistants \u201ccheap enough to run at scale\u201d will be a major task, said Jared Roesch, co-founder of generative AI group OctoAI.Options being discussed include creating a new Alexa subscription service, or to take a cut of sales of goods and services, said a former Alexa employee.Prasad said Amazon\u2019s goal was to create a variety of AI models that could act as the \u201cbuilding blocks\u201d for a variety of applications beyond Alexa.\u00a0\u201cWhat we are always grounded on is customers and practical AI, we are not doing science for the sake of science,\u201d Prasad said. \u201cWe are doing this\u2009.\u2009.\u2009.\u2009to deliver customer value and impact, which in this era of generative AI is becoming more important than ever because customers want to see a return on investment.\u201d\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"
Summarize this content to 2000 words in 6 paragraphs in Arabic Amazon is gearing up to relaunch its Alexa voice-powered digital assistant as an artificial intelligence \u201cagent\u201d that can complete practical tasks, as the tech group races to resolve the challenges that have dogged the system\u2019s AI overhaul.The $2.4tn company has for the past two<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[63],"tags":[],"class_list":{"0":"post-164867","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-tech"},"_links":{"self":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/164867","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/comments?post=164867"}],"version-history":[{"count":0,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/posts\/164867\/revisions"}],"wp:attachment":[{"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/media?parent=164867"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/categories?post=164867"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globetimeline.com\/ar\/wp-json\/wp\/v2\/tags?post=164867"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}