Google CEO Sundar Pichai speaks at the Google I/O conference in Mountain View, Calif. Google pledges that it will not use artificial intelligence in applications related to weapons or surveillance, part of a new set of principles designed to govern how it uses AI. Those principles, released by Pichai, commit Google to building AI applications that are "socially beneficial," that avoid creating or reinforcing bias and that are accountable to peopleGoogle AI Principles, Mountain View, USA - 08 May 2018

Google parent-company Alphabet beat expectations in the fourth quarter and showed off an empire that’s growing by the year. But there’s a cost to this growth plan, and it’s cutting into profits.

On Monday, the tech giant disclosed earnings of $8.95 billion or $12.77 per share on $31.85 billion of revenue over the final three months of last year. Analysts pegged it for EPS of $10.86 on $31.33 billion of revenue.

Ruth Porat, Alphabet’s chief financial officer, told analysts on a conference call: “We had a strong 2018 with total revenues of $136.8 billion up 23 percent over 2017 reflecting the benefit of our ongoing investments to deliver exceptional experiences for users and compelling returns for our advertisers partners and enterprise customers.”

Ads raked in $32.6 billion in revenues, shooting past the third quarter’s $28.95 billion — a notable victory, considering the scrutiny on Google over its approach to data privacy.

Companies like Google and Facebook collect information about users’ likes and behaviors, so they can sell targeted advertisements. But despite public backlash — which seemingly intensified over this practice or, in some cases, the access granted to outside developers and ad partners — both companies’ fourth-quarter earnings figures appeared to come out relatively unscathed.

Compared to the third quarter, Google’s ad business grew by 20 percent.

And yet, shares fell by as much as some 3 percent in after-hours trading. Apparently, the larger concern for investors is how much Google is spending to run its businesses. For instance, traffic acquisition costs (TAC) went from $6.6 billion in the previous quarter to $7.4 billion.

Mobile TAC tends to be more expensive, Porat explained, and as that business grows, so do the costs. And the company expects it to continue “to increase year-on-year reflecting ongoing strength in mobile search.”

One of the key themes across the tech companies’ earnings reports is the growing emphasis on things beyond their main devices or services. For Google, it’s called Other Bets — which include efforts like Google Fiber, Waymo and Verily — and those operating losses also jumped year-over-year, from $748 million at the end of 2017 to $1.33 billion. Meanwhile, capital expenditures exceeded expectations of $5.66 billion, coming in at $7.08 billion.

Google has been battling on multiple fronts, and fending off competitors like Amazon, Microsoft and others doesn’t come cheap. Its growing efforts extend across multiple categories, including devices — like voice-equipped smart speakers, smartphones and other gadgets — cloud computing services, connected cars, its marquee YouTube TV and video platform, and its advertising powers, among other things.

The Android maker might be used to competing in the cloud computing arena, as well as the smartphone sector — particularly now, as it seems excited about the advent of partner Samsung’s folding phones. But over the past few years, Amazon has emerged as a major rival in two critical categories: Voice assistants and advertising.

Amazon essentially defined the home-based voice assistant category, and its efforts in advertising have not only taken root, it’s growing: Revenue from the e-commerce giant’s ad business was expected to bring in less than $3 billion last year, but instead, it soared past $10 billion.

According to chief executive officer Sundar Pichai, Google plans to invest more deeply in machine learning (ML), a related area to artificial intelligence.

More development on this front can buoy several areas of its business, including advertising. Machine learning can help match up advertisers better with consumer intent and let them bid more effectively, as well as boost Google’s cloud efforts and other services.

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