Wednesday, January 14, 2026

Zacks Investment Ideas feature highlights: Alphabet, NVIDIA and Tesla

For Immediate Release

Chicago, IL – December 31, 2025 – Today, Zacks Investment Ideas feature highlights Alphabet GOOGL, NVIDIA NVDA and Tesla TSLA.

Google’s AI Renaissance (Growth Story Is Far from Over)

Zacks Rank #3 (Hold) stock Alphabet is one of the most innovative companies in the modern technological age. Over the last few years, the company has evolved from primarily a search engine provider to cloud computing, ad-based video and music streaming, autonomous vehicles, healthcare and others.

In the online search arena, Google has a monopoly accounting for roughly 90% of the online search volume and market share. Over the years, the company has witnessed an increase in search queries, resulting from ongoing growth in user adoption and usage, primarily on mobile devices, continued growth in advertiser activity, and improvements in ad formats.

AI Cannibalization Fears Overblown

Alphabet’s dominant search market share and expanding cloud footprint are key growth drivers for the company. Initially, Google’s AI efforts got off to a shaky start. For instance, in Google’s first version AI model named “Bard,” searches often were completely inaccurate.

Meanwhile, it appeared that ChatGPT and other models were running away with the AI race. However, several iterations later, and Google’s Gemini 2.5 AI delivers some of the most rapid responses in the industry and is viewed as an industry standard.

Investor fears about cannibalization of the search business are unfounded. In fact, Google’s unique hybrid AI search model has driven popularity among younger users. Gemini models are being rapidly embedded across Search, YouTube, Android, and Workspace, enhancing user experience and driving internal productivity (e.g., coding, customer service).

Google’s Groundbreaking TPU

Google has constructed its own chips to power AI bots. Google’s Tensor Processing Units (TPUs) are custom-designed Application-Specific Integrated Circuits (ASICs) built to dramatically accelerate machine learning (ML) tasks, especially large-scale training and inference for models like Google’s Gemini, powering Search, Photos, and more, available via Google Cloud and functioning as a core component of Google’s AI Hypercompute system.

A TPU board fits into the same slot as a hard drive on the massive hardware racks inside the data centers that power Google’s online services, the company says, adding that its own chips provide “an order of magnitude better-optimized performance per watt for machine learning” than other hardware options. TPU is tailored to machine learning applications, allowing the chip to be more tolerant of reduced computational precision, which means it requires fewer transistors per operation.”

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