{"id":489790,"date":"2026-05-17T22:56:14","date_gmt":"2026-05-17T22:56:14","guid":{"rendered":"https:\/\/www.europesays.com\/ie\/489790\/"},"modified":"2026-05-17T22:56:14","modified_gmt":"2026-05-17T22:56:14","slug":"the-ai-stock-with-a-10-year-head-start-that-wall-street-still-hasnt-fully-priced-in","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ie\/489790\/","title":{"rendered":"The AI Stock With a 10-Year Head Start That Wall Street Still Hasn&#8217;t Fully Priced In"},"content":{"rendered":"<p>As the expenses of building and running artificial intelligence (AI) data centers continue to surge, having lower costs is a huge advantage. One of the best ways to achieve this is with custom chips called application-specific integrated circuits (ASICs).<\/p>\n<p>ASICs for AI are hardwired chips developed for specific tasks. Not only do they cost less than <strong>Nvidia&#8217;s<\/strong> general-purpose graphics processing units (GPUs), but they are also more energy efficient, leading to significant cost savings when running <a href=\"https:\/\/www.fool.com\/terms\/a\/ai-inference\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">inference<\/a>.<\/p>\n<p>As more and more hyperscalers (owners of huge data centers) turn to ASICs for some of their AI computing needs, <strong>Alphabet<\/strong> (<a href=\"https:\/\/www.fool.com\/quote\/nasdaq\/googl\/\" class=\"font-bold hover:underline\" rel=\"nofollow noopener\" target=\"_blank\">GOOGL<\/a> 1.15%) (<a href=\"https:\/\/www.fool.com\/quote\/nasdaq\/goog\/\" class=\"font-bold hover:underline\" rel=\"nofollow noopener\" target=\"_blank\">GOOG<\/a> 1.03%) has a huge advantage in this area, having developed its tensor processing units (TPUs) more than a decade ago. The company has long run most of its internal infrastructure using its TPUs, and as such, it has optimized its entire hardware and software stack around its chips. This has given it a huge lead over competitors, most of which are still in the early days of their custom chip development. <\/p>\n<p><img alt=\"Alphabet Stock Quote\" loading=\"lazy\" width=\"64\" height=\"64\" decoding=\"async\" data-nimg=\"1\" class=\"w-full flex-none object-contain\" style=\"color:transparent\"  src=\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2026\/05\/1779058573_111_.png\"\/><\/p>\n<p>Today&#8217;s Change<\/p>\n<p>(-1.15%) $-4.60<\/p>\n<p>Current Price<\/p>\n<p>$396.47<\/p>\n<p>Key Data Points<\/p>\n<p>Market Cap<\/p>\n<p>$4.8T<\/p>\n<p>Day&#8217;s Range<\/p>\n<p>$393.18 &#8211; $399.55<\/p>\n<p>52wk Range<\/p>\n<p>$162.00 &#8211; $403.70<\/p>\n<p>Volume<\/p>\n<p>678K<\/p>\n<p>Avg Vol<\/p>\n<p>29M<\/p>\n<p>Gross Margin<\/p>\n<p>60.43%<\/p>\n<p>Dividend Yield<\/p>\n<p>0.21%<\/p>\n<p>The company introduced its eighth generation of chips in April, and for the first time, it will offer two different variations of TPUs, with one designed specifically for training and another for inference and <a href=\"https:\/\/www.fool.com\/terms\/a\/agentic-ai\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">agentic AI<\/a>. The TPU 8t, its AI model training chip, is built for pure speed, while the TPU 8i has huge memory capacity and pairs with its custom Axion <strong>Arm<\/strong>-based central processing units (CPUs). <\/p>\n<p>Alphabet&#8217;s TPUs have given it a big edge over competitors in the <a href=\"https:\/\/www.fool.com\/investing\/stock-market\/market-sectors\/information-technology\/cloud-stocks\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">cloud computing<\/a> space and AI model developers. In cloud computing, as <a href=\"https:\/\/www.fool.com\/terms\/c\/capital-expenditure\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">capital expenditure<\/a> budgets soar, the company is getting a lot more bang out of its buck than most other players, outside of perhaps <strong>Amazon<\/strong>, which also has its own chips, although not as renowned.<\/p>\n<p>Meanwhile, it has used its chips to train its world-class Gemini foundational model. By having its own chips, Alphabet can train its models and run inference at a much lower cost than competitors that rely mostly on GPUs. It then embeds its Gemini model into the rest of its business, like Search, which is helping drive growth in these areas as well.<\/p>\n<p><img alt=\"Alphabet logo.\" loading=\"lazy\" width=\"880\" height=\"587\" decoding=\"async\" data-nimg=\"1\" class=\"h-auto max-w-full rounded object-contain\" style=\"color:transparent\"   src=\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2026\/05\/1779058574_209_.png\"\/><\/p>\n<p class=\"caption\">Image source: The Motley Fool.<\/p>\n<p>The success of Alphabet&#8217;s TPUs has also allowed it to start letting select customers buy them directly from its developer partner <strong>Broadcom<\/strong> to be deployed within Google Cloud and outside its data centers. This is another huge area of growth that is just beginning. <\/p>\n<p>Time to buy the stock<\/p>\n<p>Alphabet is the most complete AI company, with its own top-notch chips and world-class AI model. Trading at a <a href=\"https:\/\/www.fool.com\/terms\/f\/forward-pe\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">forward price-to-earnings ratio (P\/E)<\/a> of 28 on 2026 estimates that likely will prove to be conservative, the market has yet to fully bake in its long-term potential. I&#8217;d still be a buyer of the stock here.<\/p>\n<p><a href=\"https:\/\/www.fool.com\/author\/20615\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">Geoffrey Seiler<\/a> has positions in Alphabet, Amazon, and Broadcom. The Motley Fool has positions in and recommends Alphabet, Amazon, Broadcom, and Nvidia. The Motley Fool has a <a href=\"https:\/\/www.fool.com\/legal\/fool-disclosure-policy\/\" class=\"text-cyan-900 hover:text-cyan-800\" rel=\"nofollow noopener\" target=\"_blank\">disclosure policy<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"As the expenses of building and running artificial intelligence (AI) data centers continue to surge, having lower costs&hellip;\n","protected":false},"author":2,"featured_media":489791,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[261],"tags":[291,289,290,18,19,17,82],"class_list":{"0":"post-489790","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-eire","12":"tag-ie","13":"tag-ireland","14":"tag-technology"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@ie\/116592390710219600","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/489790","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=489790"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/489790\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/489791"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=489790"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=489790"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=489790"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}