Google Poses a Search General Experience (SGE)

Google Labs writes (Click through for detail), had been brought  to to my attention.   Will report later on experience.  Note the specific 'generative search ' idea.    Will we buy in?

3 new ways generative AI can help you search

This week, we began opening up access to Search Labs, a new program to test out early experiments from Google — like SGE (Search Generative Experience). Once you’re in, the new generative AI powered Search experience will help you take some of the work out of searching, so you can understand a topic faster, uncover new viewpoints and insights and get things done more easily. Learn more about how to sign up to access Search Labs — and three ways generative AI can help you search.

Read more, Image , More highlights  (click thoughts above) 

For Global Accessibility Awareness Day, we shared 5 products and features built by and for people with disabilities to make the digital world more accessible. Read more >>>

AI is changing the world, and last week our President of Global Affairs Kent Walker shared our white paper with policy recommendations for how we can advance AI responsibly. Read more >>>

We also announced a Collaboration Agreement with the World Health Organization to address public health crises and scale our health impact for billions of people. Read more >>   ... '

Google Begins Opening Access to Generative AI in Search

 More from recent conference

Google begins opening access to generative AI in search

If you signed up for the Search Labs waitlist, keep an eye on your inbox.

Will Shanklin|May 25, 2023 1:55 PM   in Engadget

Google’s take on AI-powered search begins rolling out today. The company announced this morning that it’s opening access to Google Search Generative Experience (SGE) and other Search Labs in the US. If you haven’t already, you’ll need to sign up for the waitlist and sit tight until you get an email announcing it’s your turn.

Revealed at Google I/O 2023 earlier this month, Google SGE is the company’s infusion of conversational AI into the classic search experience. If you’ve played with Bing AI, expect a familiar — yet different — product. Cherlynn Low noted in Engadget’s SGE preview that Google’s AI-powered search uses the same input bar you’re used to rather than a separate chatbot field like in Bing. Next, the generative AI results will appear in a shaded section below the search bar (and sponsored results) but above the standard web results. Meanwhile, on the top right of the AI results is a button letting you expand the snapshot, and it adds cards showing the sourced articles. Finally, you can ask follow-up questions by tapping a button below the results.

Google describes the snapshot as “key information to consider, with links to dig deeper.” Think of it like a slice of Bard injected (somewhat) seamlessly into the Google search you already know.

In addition, Google is opening access to other Search Labs, including Code Tips and Add to Sheets (both are US-only for now). Code Tips “harnesses the power of large language models to provide pointers for writing code faster and smarter.” It lets aspiring developers ask how-to questions about programming languages (C, C++, Go, Java, JavaScript, Kotlin, Python and TypeScript), tools (Docker, Git, shells) and algorithms. Meanwhile, as its name suggests, Add to Sheets lets you insert search results directly into Google’s spreadsheet app. Tapping a Sheets icon to the left of a search result will pop up a list of your recent documents; choose one to which you want to attach the result.  . ... '

Google Emphasizes more Generative AI Search

Click through for more ... 

Supercharging Search with generative AI

May 10, 2023

Sign up today to test our latest update to Search, which uses generative AI to give you more information and context to your searches.

Elizabeth Reid, Vice President & GM, Search, Share

Several images of the Search Generative Experience surrounding the product logo

For the past 25 years, we’ve been devoted to the science and the craft of building a search engine. We’ve developed completely new ways to search, powered by our latest advancements in AI — whether that’s searching visually with Lens, or across modalities, using both images and text with multisearch. In fact, people now use Lens for 12 billion visual searches a month — a four-fold increase in just two years, and a growing number of those searches are multimodal.

With new breakthroughs in generative AI, we’re again reimagining what a search engine can do. With this powerful new technology, we can unlock entirely new types of questions you never thought Search could answer, and transform the way information is organized, to help you sort through and make sense of what’s out there.

Today we’re sharing a look at our first steps in this new era of Search, and you’ll be able to first try these generative AI capabilities in Search Labs, a new way to access early experiments in Search.

Improving Search with generative AI

With new generative AI capabilities in Search, we’re now taking more of the work out of searching, so you’ll be able to understand a topic faster, uncover new viewpoints and insights, and get things done more easily.

Let’s take a question like “what's better for a family with kids under 3 and a dog, bryce canyon or arches.” Normally, you might break this one question down into smaller ones, sort through the vast information available, and start to piece things together yourself. With generative AI, Search can do some of that heavy lifting for you.

You’ll see an AI-powered snapshot of key information to consider, with links to dig deeper.... 

On Perplexity.AI, Rethinking Search, Learning from the follow-up.

Played with this for some time. A different experience

 https://youtu.be/_vMOWw3uYvk?list=RDCMUCMLtBahI5DMrt0NPvDSoIRQ

PERPLEXITY AI - The future of search.

Machine Learning Street Talk

https://www.perplexity.ai/

https://www.perplexity.ai/iphone

https://www.perplexity.ai/android

Note: this was a sponsored interview and filmed on April 19th.

Interview with Aravind Srinivas, CEO and Co-Founder of Perplexity AI – Revolutionizing Learning with Conversational Search Engines

Dr. Tim Scarfe talks with Dr. Aravind Srinivas, CEO and Co-Founder of Perplexity AI, about his journey from studying AI and reinforcement learning at UC Berkeley to launching Perplexity – a startup that aims to revolutionize learning through the power of conversational search engines. By combining the strengths of large language models like GPT-* with search engines, Perplexity provides users with direct answers to their questions in a decluttered user interface, making the learning process not only more efficient but also enjoyable.

Aravind shares his insights on how advertising can be made more relevant and less intrusive with the help of large language models, emphasizing the importance of transparency in relevance ranking to improve user experience. He also discusses the challenge of balancing the interests of users and advertisers for long-term success.

Exploring the challenges and opportunities with this new search modality, Aravind highlights how blurring the boundaries between a conversational interface and a search user interface can lead to more personalized search experiences. Perplexity's vision is to create a dynamic, personalized Wikipedia-style experience for users, encouraging them to ask follow-up questions and explore related topics in an engaging loop. As users zoom in on specific details or zoom out to understand broader connections, learning becomes more efficient and tailored to individual needs.

The interview delves into the challenges of maintaining truthfulness and balancing opinions and facts in a world where algorithmic truth is difficult to achieve. Aravind believes that opinionated models can be useful as long as they don't spread misinformation and are transparent about being opinions. He also emphasizes the importance of allowing users to correct or update information, making the platform more adaptable and dynamic.

Lastly, Aravind shares his thoughts on embracing a digital society with large language models, stressing the need for frequent and iterative deployments of these models to reduce fear of AI and misinformation. He envisions a future where using AI tools effectively requires clear thinking and first-principle reasoning, ultimately benefiting society as a whole. Education and transparency are crucial to counter potential misuse of AI for political or malicious purposes.

Join us in this engaging conversation as we explore the future of AI, language models, and the transformation of learning, research, and personal knowledge management with Aravind Srinivas of Perplexity AI.

Pod version: https://podcasters.spotify.com/pod/sh...

Aravind Srinivas: 

https://www.linkedin.com/in/aravind-s...

https://scholar.google.com/citations?...

https://twitter.com/aravsrinivas?lang=en

Why You Should Not Trust AI Search Engines

Caution

Why You Should Not Trust AI Search Engines

By MIT Technology Review

February 17, 2023

Digital illustration shows a Pinocchio type character whose nose is a web search bar.

It is incredibly dangerous to combine AI language models with web search, where it is crucial to get the facts straight.

Approximately two seconds after Microsoft let people poke around with its new ChatGPT-powered Bing search engine, people started finding that it responded to some questions with incorrect or nonsensical answers, such as conspiracy theories. And Google had an embarrassing moment when scientists spotted a factual error in the company's own advertisement for its chatbot Bard, which subsequently wiped $100 billion off its share price.

The rollout of AI-based, chatbot-powered search engines promised to upend our experience of searching the web by generating chatty answers to our questions, instead of just returning lists of links. But things have not gone according to plan so far. But this came as a surprise to precisely no one who has been paying attention to AI language models.

From MIT Technology Review

View Full Article (May Require Paid Registration)

Is Perplexity AI showing us the future of search?

Future of Search?

Is Perplexity AI showing us the future of search?

Perplexity hopes to carve out a slice of the massive web search market that Google has so thoroughly dominated for 30 years.

By Mark Sullivan in FastCompany

Google’s stock price lost 3% of its value earlier this week after the New York Times published a story suggesting the search giant’s business might be threatened by generative AI. A group of new AI-powered search startups have emerged, each hoping that as powerful large language models (LLMs) improve, AI chatbots will prove a better way of scouring the web’s content than Google’s crawlers and ranking system. The most pedigreed among them, perhaps, is Perplexity AI. 

Led by CEO and cofounder Aravind Srinivas, the San Francisco-based startup boasts a who’s who of AI luminaries among its investors: People like neural network pioneer and Turing Award winner Yann LeCun (now chief scientist at Meta AI), Ashish Vaswani (lead inventor of the transformer models that power new AI chatbots, including OpenAI’s ChatGPT), Jeff Dean (who currently leads Google’s AI research), OpenAI founding member Andrej Karpathy, and early AI angel investors Elad Gil and Nat Friedman.

Perplexity, like other new AI search-bots, including Microsoft with its Bing Chat, hopes to one day carve out a slice of the massive web search market that Google has so thoroughly dominated for 30 years. Google made $162 billion last year from search advertising and licensing.  

AI search-bots represent a fundamentally different approach to retrieving content from the web. Google works by matching search queries with relevant sites that its web crawlers have found and indexed, then ranking those content sources based on their popularity and other factors. AI “answer engines” (as Perplexity terms them) leverage the language skill of large language models (LLMs) to understand queries, then assemble customized, conversational answers based on content from the millions of web pages to which the LLM was exposed during training. 

Actually, Perplexity uses both approaches. “When you type in a question at Perplexity it’s going to look into a search index and pull up the relevant web pages—the top few web pages and the snippets,” says Srinivas, who worked at both Google’s DeepMind and Google Research, then at OpenAI before founding Perplexity. “Then it’s going to pass it into a chatbot LLM that’s going to look at all that and find out what’s actually useful to the query.” 

Srinivas says Perplexity’s secret sauce may be the careful balance it’s struck between indexing/ranking and LLM-based search. “It’s very hard to identify the sweet spot between a canonical search engine that always gives you the links—and it’s pretty trustworthy, but not very productive in terms of directly getting what you want—and a hallucinatory ChatGPT that’s very easy and fun to use but you may not find the trust to actually believe what it says.” 

Perplexity’s deals with LLMs’ habit of hallucination (i.e. making things up) by placing a strong emphasis on citations and references. The results from the initial query and all follow-up queries are always accompanied by such notations, and they can be clicked upon to ask follow-up questions or dig deeper into topics.

“We come from an academic background and we have this core principle that when you write a paper you are not allowed to say things that you cannot cite,” Srinivas explains. “That’s a core tenet of Perplexity . . . we basically told the LLM to never say anything it cannot back up.”   ... ' 

Considering Fact Checking on Google Search

Its Fact Checking Day!

The topic comes up again,  How do we do this well?  Oddly though not a thing about 'Bard' where it has come up too.

Five new ways to verify info with Google Search   Mar 28, 2023

Itamar Snir,  Product Manager, Google News

Nidhi Hebbar, Product Manager

This illustration shows a Google "g" in the middle of different visualization of features people could see across our surfaces

People come to Google to find information quickly, understand complex topics and to parse facts from fiction. Google Search helps people find high-quality information from around the world, from a variety of diverse and credible sources, and find new perspectives to help them better understand the world. But sifting through all of the content available on the web can feel overwhelming, especially when you're trying to determine what information you can rely on.

International Fact-Checking Day on April 2 is a call to action – because in this day and age, nearly everyone has found themselves needing to put on their own fact-checking hat to verify a claim or check a source. Everyone should be empowered with the tools they need to find information they can trust. That’s why we build features to help you evaluate the information you come across online while expanding the range of helpful information you can find. Today we’re sharing how we’re expanding and improving these resources on Google Search.

Learn more with About this result – now available globally

When you search on Google, you probably see results from a number of websites and sources that you recognize – maybe it’s your favorite store or a blog you read regularly. But there also might be sites or sources that you haven’t come across before or aren’t as familiar with. To help people evaluate information and understand where it’s coming from, our About this result feature will be available in all languages where Search is available in the coming days. Now, wherever you’re searching, you’ll see three dots next to most results on Google Search. Tapping those three dots gives you a way to learn more about where the information you’re seeing is coming from and how our systems determined it would be useful for your query. With this context, you can make a more informed decision about the sites you may want to visit and what results will be most helpful for you. ... ' 

Microsoft to Ruin Chat Search?

Ouch if this is the case. 

ChatGPT Opened a New Era in Search. Microsoft Could Ruin It

By Wired, March 31, 2023

Microsoft in February announced its standard fees for search data would increase by as much as 10 times starting in May.

Google typically gets the blame for the lack of competition in web search. The US government is even suing to block the company from using allegedly monopolistic tactics, like making itself the default search engine in widely used software such as Android, Chrome, and Safari.

But some upstart search engines trying to woo users with privacy protections or ad-free searches say their latest challenge doesn't come from Google. Instead, it's Microsoft and its Bing search engine causing their aggravation.

Search startups have long relied on licensing search results from Bing, tapping a web indexing operation larger than a small company could easily afford and adding their own features and ways of parsing queries. But Microsoft's rollout of a Bing search chatbot based on technology underlying OpenAI's ChatGPT has prompted concerns that Microsoft is unfairly squeezing out its search data customers as it launches a renewed attempt to bite off more market share from Google.

From Wired

View Full Article  

Big Point being made, Will Search be completely Revolutionized, and Implications.

 One look at this:, what are the key issues?    

Generative AI Won’t Revolutionize Search — Yet        by Ege Gurdeniz and Kartik Hosanagar   in HBR 

Summary.   Generative AI has the potential to drastically change what users expect from search, and companies such as Microsoft and Google are placing big bets on what it might yield. But despite the hype around ChatGPT — and generative AI overall — there are major...more

ChatGPT has created a frenzy. Since the release of OpenAI’s large language model (LLM) in late November, there has been rampant speculation about how generative AIs — of which ChatGPT is just one — might change everything we know about knowledge, research, and content creation. Or reshape the workforce and the skills employees need to thrive. Or even upend entire industries!

One area stands out as a top prize of the generative AI race: search. Generative AI has the potential to drastically change what users expect from search.

Google, the longtime winner of online search, seems to suddenly have a challenger in Microsoft, which recently invested $10 billion in ChatGPT’s developer, OpenAI, and announced plans to incorporate the tool into a range of Microsoft products, including its search engine, Bing. Meanwhile, Google is releasing its own AI tool, Bard, and Chinese tech giant Baidu is preparing to launch a ChatGPT competitor. Millions of dollars are being poured into generative AI startups as well.

But despite the hype around ChatGPT — and generative AI overall — there are major practical, technical, and legal challenges to overcome before these tools can reach the scale, robustness, and reliability of an established search engine such as Google. ... ' 

If Search is Really Reinvented

Seen from the retail direction, if Search is reinvented significantly, what will that mean?  Faster, more accurate?   Supply chains?   Search engine optimization certainly.    Mused about in pundits from Retailwire.  

Will ChatGPT reinvent search?  by Tom Ryan

Microsoft and Google both revealed plans last week to introduce their own ChatGPT-style product, joining the hype around the AI-driven chatbot technology.

Developed by San Francisco-based startup OpenAI and introduced last November, ChatGPT taps generative artificial intelligence to provide people with human-like responses to their questions. The technology also generates a wide range of digital text that can be repurposed in nearly any context, including in tweets, blog posts, term papers, poetry and even computer code.

Microsoft, which is investing $10 billion in OpenAI, will integrate ChatGPT technology with its Bing search engine and Edge web browser

Brad Smith. vice chair and president of Microsoft, said in a blog entry, “Today’s cutting-edge AI is a powerful tool for advancing critical thinking and stimulating creative expression. It makes it possible not only to search for information but to seek answers to questions. It can help people uncover insights amid complex data and processes. It speeds up our ability to express what we learn more quickly. Perhaps most important, it’s going to do all these things better and better in the coming months and years.

Google will soon offer an AI and natural language-enhanced version of its Google search engine called Bard, as well as a chatbot.

However, Microsoft created more buzz, having introduced a limited version of the new Bing available to some users this week to rave reviews and drawing predictions that Bing may threaten Google’s search dominance.

Microsoft’s CEO Satya Nadella said at a media event, “This technology is going to reshape pretty much every software category.”

In China, JD.com, Alibaba and Baidu confirmed they are working on ChatGPT-style projects, as well. Meta is also planning to release similar technology across various products.

Microsoft said its search engine includes technology that identifies and removes problematic content from the chat service. However, the A.I. technologies are known for often producing toxic content, including misinformation, hate speech and biases against women and people of color.  ... ' 

On the AI Money War

 On the AI wars, well put, who can win and how much. Is simple search fundamentally over?

The AI wars: Google vs Bing (ChatGPT)  By Sendex

1.21M subscribers, 96,895 views  Feb 11, 2023

Discussing the latest events surrounding large language models, chatbots, and search engines with respect to Microsoft and Google.

Neural Networks from Scratch book: https://nnfs.io

Channel membership: https://www.youtube.com/channel/UCfzl...

Discord: https://discord.gg/sentdex   ... 

(mentions other alternative models beyond Msoft and Google)  ... 

Malvertizing Search

Now reemerging,  imagine Google is very concerned.   

Until further notice, think twice before using Google to download software

Over the past month, Google has been outgunned by malvertisers with new tricks.

Dan Goodin

Searching Google for downloads of popular software has always come with risks, but over the past few months, it has been downright dangerous, according to researchers and a pseudorandom collection of queries.

“Threat researchers are used to seeing a moderate flow of malvertising via Google Ads,” volunteers at Spamhaus wrote on Thursday. “However, over the past few days, researchers have witnessed a massive spike affecting numerous famous brands, with multiple malware being utilized. This is not ‘the norm.’”

One of many new threats: MalVirt

The surge is coming from numerous malware families, including AuroraStealer, IcedID, Meta Stealer, RedLine Stealer, Vidar, Formbook, and XLoader. In the past, these families typically relied on phishing and malicious spam that attached Microsoft Word documents with booby-trapped macros. Over the past month, Google Ads has become the go-to place for criminals to spread their malicious wares that are disguised as legitimate downloads by impersonating brands such as Adobe Reader, Gimp, Microsoft Teams, OBS, Slack, Tor, and Thunderbird.  ... ' 

Examining Google's Near Monopoly Search

 Call for a reinvention of Web search.

Check out all the on-demand sessions from the Intelligent Security Summit here.    in Venturebeat

The internet turns 53 this year, and it has been profoundly shaped by Big Tech companies ... 

(parts of my look at the problem of web search driven by consumer data, the implications) 

As the internet advances into middle age, Google is currently in control of an incredible amount of the world’s access to information on the internet. Users across the globe appear to be constantly served “free content;” however, there’s a hidden fee for this content served up by a company that has more than 90% market share. 

Google’s success in search advertising, as well as its relentless focus on driving advertising on the web, has created a toxic web environment where everything we do is surveilled. What we do in a search and even beyond is packaged and used for advertising, and it is extremely difficult to tell the authentic and trustworthy from the attention-grabbing and deceptive.

But search doesn’t need to be this way. Consumers and enterprises alike can benefit from a bespoke web experience that serves up genuinely helpful answers to searches, not advertisers shilling the wares they want to unload today.

Intelligent Security Summit On-Demand

Learn the critical role of AI & ML in cybersecurity and industry specific case studies. Watch on-demand sessions today.

Here’s how we go about reinventing web search?  ... 

Reduce ad noise by subscribing to an alternative search model ... 

Subscription services undoubtedly benefited from the pandemic. People signed up to Netflix, Disney+ and others in droves. Meanwhile, premium publishers shifted the majority of their content behind a paywall. People have grown accustomed to subscription services, as it doesn’t just extend to entertainment, but fitness classes, home cooking kits, software, skincare — the list goes on. The takeaway from subscription economy growth: People want products to deliver the best experience for them and not a persona that Google has created based on their buying preferences.

Web searches shouldn’t be any different. After all, it’s the way we access knowledge, and it informs our opinions. 

A search subscription model would make ads redundant. With no advertisers to please, the focus is put back on users, which means that companies can focus on making search experiences more accurate and intuitive. Users pay a small monthly fee in exchange for unbiased search results and a product where privacy becomes a de facto foundation; which is good news for everyone.

However, shifting to a subscription model at scale and eradicating ads in search is certainly not without its challenges. It’s why Google still has the monopoly on web search today. But it’s also not a dystopian future out of our reach.   ...  '

Microsoft Plans to Add ChatGPT to Bing

 Can ChatGPT be successfully be integrated into services like search engines?  Implications?  Will public uses be useful, dangerous? 

Microsoft Plans to Add ChatGPT to Bing Search Engine: Report

By Eric HAL Schwartz on January 4, 2023   in Voicebot.ai

Microsoft will incorporate ChatGPT into its Bing search engine, according to a report from The Information. The OpenAI synthetic media chatbot will serve to answer questions directly instead of the traditional link list and could debut as soon as the end of March in an attempt to come out ahead of Google’s far more widely used search engine.

BING CHATGPT

Bing has always run far behind Google as a search engine, even as a term for searching online. ChatGPT’s recent explosive popularity could change that equation. Microsoft’s $1 billion investment into OpenAI includes an exclusive claim to enterprise applications like a ChatGPT-based search engine so it would have an edge over Google. The idea seems to be an alternative version of Bing where users could converse with ChatGPT and get direct answers, including on recent developments, with sources cited and hyperlinked. The currently available version of ChatGPT explicitly states it is trained only on data as recent as a year ago. Microsoft had been supposedly working on a chatbot for Bing as long ago as 2021, but this appears to be a different product entirely.

Microsoft has already begun incorporating other OpenAI tools into Bing. The tech giant began making the DALL-E text-to-image service part of Microsoft 365 through the new Designer app and the upcoming Image Creator tool for both Bing and Edge. Google has plenty of large language model projects of its own in the works through Deepmind, but hasn’t made anything like ChatGPT available to the public.

CHATBOT SEARCH

Microsoft would also not be the first on the scene with a ChatGPT-style search engine, although certainly the largest and first with ChatGPT actually backing it. You.com recently launched the YouChat search engine, capable of sourcing current events through generative AI. You.com is smaller than Bing, let alone Google, but it does demonstrate there’s at least some interest in a search engine with a conversational format. ChatGPT was already seeing potential rivals in GPT-3-derived chatbots, such as Jasper Chat, a chatbot format for Jasper’s own generative AI engine. Google may face some real competition in the search sector for the first time in a very long time if Bing and others experimenting with this approach take off.  ...

Are Ads Causing Shoppers to Lose Faith in Amazon search results?

 Significantly?

Are ads causing shoppers to lose faith in Amazon search results?   by Matthew Stern in RetailWire.

Amazon.com has long been the main go-to place for online product search, but a recent Washington Post article finds that it is no longer giving customers what they want because advertisements are muscling out the real search results.

Running a search for “cat beds,” the Post found that the entire first screen of results displayed advertisements masquerading as listings rather than products arrived at because they provided the best combination of price and quality. The results included one ad that featured a dog in the picture, rather than a cat.

On the first five pages of search results, more than half of the listings were either ads or Amazon’s own products. A Profitero study found that Amazon lists sponsored products on its first page of search results at a rate twice that of Walmart and four times that of Target. Other online outlets, like food delivery platforms and Google and Apple’s app stores, have also started displaying ads as search results.

Amazon’s ad business grew 58 percent in 2021, making it the third largest online ad seller, according to a Recode article. Six high-volume sellers told Recode that to succeed on Amazon today, sellers have to spend between 10 and 20 percent of their sales on ads.

Amazon’s practices surrounding how it lists search results have been criticized before. ... ' 

Fairer Search Results

 Ranking, Fairness. 

Fairer Ranking System Diversifies Search Results

Cornell Chronicle

Patricia Waldron,  September 19, 2022

Cornell University researchers Yuta Saito and Thorsten Joachims have developed a fairer ranking system for recommendations that prevents search results from only highlighting a few top hits. Conventional recommender systems try ranking items based on what users want to see, so Saito designed the enhanced ranking system according to the economic principles of "fair division." The researchers used synthetic and real-world data to test the system's feasibility. The system returns viable results that rank items' benefits better than random discovery, does not easily improve items' impact, and does not confer an advantage to any item by switching how it is ranked versus other items in a series of searches. Saito said the framework "can be applied to any type of two-sided ranking system."

Boutique Search Again

Reminds me of the early days of search and things we set up for specialty use.   Especially healthcare based, but could be related to any domain.    Curated web and supporting search engines.    Recall setting up a search engine pointed (curated to) directly at a specific project.   See 'Zakta' as an example, is it still available? 

The Future of Search Is Boutique, By Sari Azout in future.a16z

This is an edited version of a post that originally ran here. 

For most queries, Google search is pretty underwhelming these days. Google is great at answering questions with an objective answer, like “# of billionaires in the world” or “What is the population of Iceland?” It’s pretty bad at answering questions that require judgment and context like “What do NFT collectors think about NFTs?”

The evidence is everywhere. These days, I find myself suppressing the garbage Internet by searching on Google for “Substack + future of learning” to find the best takes on education. We hack Twitter with the “what is the best” posts over and over again. When I’m researching a new product, I type “X item reddit” into Google. I find enormous value in small, niche, often forgotten sites like Spaghetti Directory.

There’s an emergence of tools like Notion, Airtable, and Readwise where people are aggregating content and resources, reviving the curated web. But at the moment these are mostly solo affairs — hidden in private or semi-private corners of the Internet, fragmented, poorly indexed, and unavailable for public use. We haven’t figured out how to make them multiplayer. In cases where we’ve made them public and collaborative — here is a great example — these projects are often short-lived and poorly maintained.

The stated mission of a company worth almost two trillion dollars is to “organize the world’s information” and yet the Internet remains poorly organized. Or, stated differently, in a world of infinite information, it’s no longer enough to organize the world’s information. It becomes important to organize the world’s trustworthy information.  .... ' 

MUM a new way to search online.

Is MUM just like a conversation online?   Most interesting. I  just recently noticed the amount of searching I had to do just to get background info.  

This new AI tool from Google could change the way we search online  by 7wData

What does the future of internet search look like? Google envisions it as looking more like a casual conversation with a friend. 

While Google’s search engine has been online for over two decades, the technology that powers it has been constantly evolving. Recently, the company announced a new artificial-intelligence system called MUM, which stands for Multitask Unified Model. MUM is designed to pick up the subtleties and nuances of human language at a global scale, which could help users find information they search for more easily or allow them to ask more abstract questions.  

Google already used MUM in an independent task to learn more about the different ways people refer to COVID vaccines, but says that the new tech is not yet part of their search system. While there’s currently no set timeline on when the feature will roll out in live search, the team is actively working on developing other one-off tasks for MUM to complete. 

Here’s what to know about what MUM is, how it’s different from what’s come before, and more.   ... '

Search is not a Conversation Yet

Search as AI,  and fundamentally conversation, putting it all together.    Google started with search, while the assistant providers started with the conversation.  Moving in the right direction. 

Google isn’t ready to turn search into a conversation

Despite Google’s whizzy AI demos at I/O, search is still served best by text  By James Vincent 

The future of search is a conversation — at least, according to Google.

It’s a pitch the company has been making for years, and it was the centerpiece of last week’s I/O developer conference. There, the company demoed two “groundbreaking” AI systems — LaMDA and MUM — that it hopes, one day, to integrate into all its products. To show off its potential, Google had LaMDA speak as the dwarf planet Pluto, answering questions about the celestial body’s environment and its flyby from the New Horizons probe.

GOOGLE’S DREAM IS TO SPEAK AND THE MACHINE WILL ANSWER

As this tech is adopted, users will be able to “talk to Google”: using natural language to retrieve information from the web or their personal archives of messages, calendar appointments, photos, and more.

This is more than just marketing for Google. The company has evidently been contemplating what would be a major shift to its core product for years. A recent research paper from a quartet of Google engineers titled “Rethinking Search” asks exactly this: is it time to replace “classical” search engines, which provide information by ranking webpages, with AI language models that deliver these answers directly instead?

There are two questions to ask here. First is can it be done? After years of slow but definite progress, are computers really ready to understand all the nuances of human speech? And secondly, should it be done? What happens to Google if the company leaves classical search behind? Appropriately enough, neither question has a simple answer.  ... 

P&G Admits What Worked, What Didn't in Pandemic

Some rare inside information re Digital details from my former colleagues at P&G.  Recall I have mentioned here that P&G was an early pioneer in AI based methods.  Its good you can admit to what did not work.  Lets you adjust your directions and methods in the future. 

P&G's Benjamin Spiegel Admits What He Got Wrong

The global chief digital officer also discussed AI, 'maskne,' virtual influencers and the lipstick effect.

By Paul Hiebert   in AdWeek

Benjamin Spiegel, global chief digital officer for Procter & Gamble’s beauty segment, is not afraid to admit that some changes in consumer behavior he thought might occur during the pandemic … well, did not occur.

“There were a lot of things that we assumed would happen early on that, in the end, didn’t quite pan out,” noted Spiegel while speaking at Adweek’s Elevate: AI summit.

One was an expected boom in direct-to-consumer shopping. Instead, Spiegel explained, retailers got creative and have updated their click-and-collect and last-mile delivery options. “That was a big one for me that I got totally wrong,” he said.

Another prediction was that people would struggle with working at home—that the ideas, creativity and collaboration just wouldn’t be there. While remote work certainly has its challenges, Spiegel said people have shown resilience and embraced new technology that enables workers to get the job done.

Spiegel said the company has begun thinking about campaigns as “always on,” as opposed to initiatives that start and stop. “The time[s] of day where people make decisions [and] consume content have definitely changed,” he said.

P&G has also tracked the popularity of certain search terms, such as “maskne” (i.e. acne caused by wearing a face mask), and responded with tailored messaging and educational content. Usually, trends come and go, Spiegel said, but trends during Covid-19 had a “big impact on how people thought about product and usage.”

The lipstick effect—the theory that shoppers still spend money on small indulgences during economic downturns—is still going strong during the pandemic, Spiegel said. For example, their research found that instead of buying a piece of clothing that costs $200, consumers would purchase a $40 beauty product.

“People went into saving money in certain places, but then they ended up spending more in other places,” he said.

For the quarter ending March 31, P&G’s beauty business, which includes the brands Olay, SK-II and Old Spice, saw net sales climb to $3.3 billion, up 9% compared to the same period in 2020.  ... '