Is a ChatGPT Killer Coming from Google?

Is a ChatGPT Killer Coming from Google?

by Mark Smith Artificial Intelligence Google

It looks like the AI arms race is heating up.

Google is expected to announce soon the launch of a competitor to ChatGPT, the generative AI tool that has shaken the technology and business world.

ChatGPT is the product of OpenAI, the company that produced Dall-E, which uses AI to create images. ChatGPT is one of many chatbots designed to respond to queries from people by providing richer, more detailed, and more human-sounding answers than their predecessors. The incredibly slick bot uses AI to do everything from write copy to answer search queries to write code.

Some technology/business watchers have speculated that ChatGPT is a threat to Google Search. That’s because ChatCPGT responds to queries with a single answer that synthesizes information, which could upend how Google Search provides answers with links to information. Moreover, OpenAI is receiving deep funding from Google competitor Microsoft, which is incorporating the tool in its products, including, reportedly, Bing Search.

Well, Google has not taken the rise of ChatGPT lightly. Google’s parent Alphabet announced its quarterly earnings recently, and Alphabet CEO Sundar Pichai said that Google is working on its own form of smart search. He said that “very soon people will be able to interact directly with our newest, most powerful language models as a companion to Search in experimental and innovative ways.”

Apparently “very soon” is almost here. On February 8, Google is hosting an event on YouTube, which will revolve around “using the power of AI to reimagine how people search for, explore and interact with information, making it more natural and intuitive than ever before to find what you need.”

Releasing an answer to ChatGPT is not far-fetched. Google has contended that it has been developing AI-powered search technology for quite some time but is not ready to share it publicly. Examples of Google’s AI-driven products include a chatbot language model called LaMDA (Language Model for Dialogue Applications), an image-generation AI called Imagen, and MusicLM, which translates text to music.

But when OpenAI seized the narrative about generative AI by releasing ChatGPT in November 2022, reportedly Google went into “Code Red” mode and began fast tracking the development of various AI products.

Google has reportedly asked employees to test potential ChatGPT competitors, including “Apprentice Bard,” which makes it possible ask questions and receive detailed answers similar to ChatGPT. Details about Apprentice Bard’s functionality were leaked to CNBC, which reported:

Apprentice Bard looks similar to ChatGPT: Employees can enter a question in a dialog box and get a text answer, then give feedback on the response. Based on several responses viewed by CNBC, Apprentice Bard’s answers can include recent events, a feature ChatGPT doesn’t have yet.

Meanwhile, recently it was reported that Google has invested $300 million in AI startup Anthropic, which is testing a rival to OpenAI’s ChatGPT. Anthropic’s language model assistant, Claude, hasn’t yet been released to the public, but the startup told Bloomberg it planned to expand access to the chatbot “in the coming months.”

One way or another, Google is gearing up to respond – although the impact of a chat-powered AI tool on Google’s paid search business remains unclear.

At True Interactive, we are following these developments closely. We already use Google’s AI-powered ad products. Based on our experiences with AI, we strongly advise that businesses experiment with these tools carefully.

We also recommend that businesses keep people involved in managing AI (or any technology). People are needed more than ever to ensure that AI does its job well. For instance, our experience has consistently shown that automated ads powered by AI underperform without people involved to monitor and modulate them when necessary. The same is true of generative AI. These tools sure sound confident when they present information, but they make mistakes, and they are notoriously biased. They are nowhere near the point of being self-sufficient.

We’ll follow the developments from Google and report back on our blog.

Contact True Interactive

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What Is Machine Learning?: Advertiser Q&A

What Is Machine Learning?: Advertiser Q&A

by Mark Smith Artificial Intelligence

Machine learning is affecting the way businesses operate – including how they advertise. Google, for instance, uses machine learning to help businesses optimize the performance of their search ads. But not everyone understands exactly what machine learning is. We thought we’d take a moment to break the topic down and answer some common questions.

What is machine learning?

Machine learning is a type of artificial intelligence (AI) in which computers literally have the ability to learn, and subsequently make increasingly more intelligent decisions. The learning happens when a computer program accesses and analyzes data — data in amounts generally too vast for humans to read through quickly or accurately. The computer looks for patterns in the data and learns automatically, without human assistance. Spotify, for instance, uses machine learning to understand the musical tastes of its subscribers in order to recommend songs that are more likely to match their interests.

Is machine learning the same as AI?

Machine learning is one aspect of AI. AI in fact encompasses many things, including:

  • Natural language processing, or NLP, a technology that equips machines to interpret what people say in words or text. Advanced NLP not only deciphers speech, it teases out context and detects nuances like sarcasm.
  • Chatbots, the programs operating inside messaging apps or on websites, which allow consumers to accomplish simple tasks like e-commerce transactions.
  • Neural networks, which are AI programs that use the human brain as a model. Neural networks incorporate aspects of AI like NLP in order to perform duties such as recognizing handwriting.
  • Dynamic pricing, in which programs use consumer data to set prices that are most likely to ensure a sale given various factors.
  • Content Curation, an aspect of AI that can be used to figure out what specific goods to recommend to consumers based on data about that consumer.

In short, AI is a supercategory describing and encompassing the many ways computers emulate the way people think and act. In the vast universe of AI, machine learning is one subcategory.

How are businesses using machine learning in online advertising?

Machine learning can help businesses test the effectiveness of different forms of advertising. Not only can it prioritize ads that are doing better, machine learning can even pinpoint what ads are performing best at certain times.

Google’s efforts to stay competitive in a field shared by powerhouses such as Amazon and Facebook exemplify an effective use of machine learning. As we recently discussed, Google’s responsive search ads and responsive display ads make it possible for advertisers to enter multiple headlines, descriptions, and logos. Machine learning figures in by automatically testing various combinations of these factors and highlighting the ads that perform best.

What are some tips for succeeding with machine learning?

Like any tool, machine learning can be used wisely—or abused. To glean the best results, keep in mind that:

  • Machine learning is not a replacement for humans. Use it as a complement to human judgment.
  • Machine learning is a dynamic field. This is not a topic you can learn once and then consider it mastered. Machine learning tools evolve quickly, with new ones coming along seemingly on a weekly basis. Stay on top of the changes.

Contact True Interactive

Curious as to how machine learning can help you with your digital advertising? Contact us.

Photo by Franck V. on Unsplash

Get Ready for AI Everywhere

Get Ready for AI Everywhere

by Mark Smith Artificial Intelligence

In 2019, artificial intelligence (AI) will make digital advertising more targeted, thanks in part to the efforts of Google. But marketers will need to invest more time and effort to make AI pay off.

It’s clear that AI is essential to Google’s growth. In February 2018, CEO Sundar Pichai said AI is more profound than electricity or fire. A few months later, he published a statement of AI principles in which he outlined seven ways Google will use AI (and ways that Google will not). The post focused on the importance of using AI for social good. Pichai did not mention using AI for advertising, but Google is certainly applying AI to make advertising smarter.

For instance, in 2018, Google launched a number of products that use machine learning (a form of AI) to improve online advertising performance. I recently blogged about one such product, responsive search ads. As I noted, responsive search ads make it possible for advertisers to enter multiple headlines (up to 15) and descriptions (up to four) when creating a search ad. Then Google Ads applies machine learning to automatically test different combinations and learn which combinations perform best. In addition, per Google, advertisers can add a third headline and second description to your text ads, and your descriptions can have up to 90 characters.

2018 was just a warm-up for what’s to come in 2019. Businesses demand more accountability and ROI from their online ad spend, and AI does just that. I expect Google will focus more on using AI to make YouTube more effective. Google has already injected AI into YouTube with features such as maximize lift, which is a smart bidding tool that automatically adjusts bids at auction time to maximize the impact a company’s video ads have on brand perception. Maximize lift is supposed to help businesses reach people who are most likely to consider their brand after seeing a video ad.

One concern we often hear from advertisers is that YouTube is not as useful for direct-response campaigns as it is for brand building. In 2019, we’ll see the emergence of tools that do a better job targeting video ad content to people who are in shopping mode and ready to buy as Google makes YouTube more of a lower-funnel platform.

AI will make online advertising better. But AI will also require marketers to invest more time and energy to make it pay off, as I discussed in my post about responsive search ads. It’s important that businesses understand its uses and requirements. For more insight, contact True Interactive. We help businesses maximize the value of their online advertising and understand where the industry is headed.

Image source: https://pixabay.com/en/artificial-intelligence-robot-ai-ki-2167835/