Elon Musk’s quiet, untweeted China trip

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We usually hear too much about what Elon Musk’s up to lately, but you may have missed the news last week that he paid a three-day visit to China and met with quite a few high-ranking government officials there.

Ever since China lifted most of its pandemic-era travel restrictions in January, foreign executives have been swarming in. And Musk had good reason to go: China is a vital part of Tesla’s electric-vehicle empire, both as a market and as a production powerhouse. But as the owner of Starlink, SpaceX, and recently Twitter, Musk has a much more complicated relationship with the country.

There’s little information in English about Musk’s China trip. That’s primarily because Musk, usually active on the social media platform he just acquired, stayed very quiet during the whole trip. While Twitter is banned in China, people have all sorts of VPN tools to access it. Still, Musk didn’t seem to want to give the impression that he was on Twitter while there. He only tweeted a single time about the trip, after he left China. In fact, he even stopped commenting on other tweets—something he normally does dozens of times every day. 

But from the public readouts posted by Chinese government websites and sightings of Musk shared on Chinese social media, we can reconstruct his trip from Tuesday to Thursday.

He had quite a busy itinerary: in 44 hours, Musk met with at least three high-level Chinese officials, dined with the CEO of the world’s largest EV battery supplier, and visited Tesla’s factory in Shanghai, among other things. 

Musk’s private jet landed in Beijing on the afternoon of May 30, local time. He met with Qin Gang, China’s new foreign minister and previous ambassador to the US, the same day. According to the ministry’s press release, Musk said in the meeting that he strongly opposes decoupling supply chains between the US and China, because the two countries are “interlinked, like conjoined twins inseparable from each other.” That evening, he had dinner with Zeng Yuqun, the CEO of CATL, which is a key supplier of batteries to Tesla cars. 

Musk holding hands with Qin Gang, China's Minister of Foreign Affairs


The next day, he met with two more Chinese ministers, those in charge of commerce and technology. Reuters reported that he also visited Vice Premier Ding Xuexiang—China’s sixth-highest-ranking party official—that afternoon, but the meeting has not been made public by the government or Musk. In the evening, he flew to Shanghai and headed to the Tesla Gigafactory, where he took photos with employees that he would later post on Twitter.

Elon and the team of the Shanghai gigafactory pose for a group photo


On the morning of June 1, his last day in China, Musk squeezed in one last meeting with Chen Jining, the Shanghai party secretary, before his jet left for Texas at 11:23 a.m.

Musk is not the first American executive to visit China this year: before him, there were Apple’s Tim Cook, General Motors’s Mary Barra, JP Morgan’s Jamie Dimon, Starbucks’s Laxman Narasimhan, and more. But so far, Musk has received the biggest welcome, both from Chinese government officials and from the people on Chinese social media.

The main reason is that China and Tesla have been in a mutually beneficial relationship for years. Not only is China the second-largest market for Tesla, but the Shanghai Gigafactory produced over half of Tesla cars sold globally last year. On the other end, the Shanghai factory also contributed significantly to local employment and taxation, as well as making the city a hub of EV production.

During the strict one-month lockdown in Shanghai last year, the municipal government made extra arrangements to make sure the factory could resume production even while other parts of city life were on pause. During this visit, Musk acknowledged those efforts and thanked the Chinese commerce minister.

But there are other things that complicate the relationship between Musk and China.

For one thing, Starlink has long been a concern for Beijing because of its capacity to circumvent traditional communication blackouts and offer additional satellite intelligence. Its application in Ukraine during the war, in which China largely stands on the side of Russia, has made the issue clearer. Earlier this year, it was reported that researchers in China’s military academies have published dozens of papers on how to work against the Starlink satellites. 

On Weibo, the Chinese equivalent of Twitter, Musk (or whoever operates his verified account) posted a note on May 30 that seemed designed to smooth things over a little: “The China space program is far more advanced than most people realize.”

At the core of Musk’s complicated relationship with China is the fact that his different companies have different relationships with the Chinese government. Tesla is exceptionally welcome in the country; Twitter is a big headache for the government and is strictly banned; SpaceX and Starlink are somewhere in between, representing both a security risk and a collaboration opportunity. 

So far, his ownership of the other companies hasn’t caused Tesla to fall out of favor in China. But in this age of sustained US-China tensions, dealing with the Chinese government is a very delicate act for any American company, and Tesla will probably be a bellwether. No matter how much trolling he likes to do in the US, Musk had to be more cautious when he was in China.

What do you think of the trend of American business executives visiting China? Let me know your thoughts at zeyi@technologyreview.com.

Catch up with China

1. Montana’s TikTok ban could be another “junk internet bill”—highly politicized and unlikely to survive judicial review. (MIT Technology Review)

2. Sunday marked the 34th anniversary of the protest and massacre in Tiananmen Square. 

  • Every year in Hong Kong, people have gathered in a public park to hold a vigil. This year, the vigil was blocked by a food carnival hosted by pro-Beijing groups in the same park. (Wall Street Journal $)
  • People who tried to take candles out were taken away by police. (Reuters $)
  • The vigils and protests have been carried on by people overseas. (CNN)

3. Shein, the Chinese fashion e-commerce company that has attracted a large Gen Z following, has hired Washington lobbyists for the first time, to respond to allegations of forced labor practices. (Politico)

4. Defense officials around the world are gathering in Singapore this week for the high-level Shangri-la Dialogue. (CNBC)

  • Meanwhile, spy masters are having a separate, secret meeting in the same city. (Reuters $)
  • CIA director Bill Burns also had a secret trip to China last month, meeting Beijing’s intelligence officials. (Financial Times $)

5. As Pride month begins, China’s LGBTQ communities are losing their few support groups as they are squeezed by the government to shut down operations. (The Economist $)

6. Local police in China are increasingly dealing with a new type of scam: people are using generative AI tools to impersonate others and request money transfers from the victim’s contacts. (Wall Street Journal $)

Lost in translation

Would you spend $1 a month to have unlimited chats with a simulacrum of your favorite influencer? Xiaoice, a Chinese AI company, just offered this service. Every Thursday from now on, the company will release a new “AI clone” of a Chinese influencer (the first is designed around a 20-something female model named Hu Wenjie, better known by her online alias 半藏森林). Users can converse by text and voice with such AI chatbots. If they spend 30 RMB ($4.22) a month, the “influencer” will double as an office assistant and help with tasks like writing marketing copy. (Why would you want your influencer to do that?) The service has a strong romantic tone: the basic subscription is called the “relationship mode.” For now, the majority of the profits go to the influencer, according to a report by Chinese state broadcaster CCTV.

One more thing

The latest viral social media trend in China is packing a lunch that’s simple and sometimes too bland to eat and calling it 白人饭—literally, “white people food.” It’s surely a dig at the quick lunches in American food culture, but there are also people who say they’re doing it to lose weight or to forgo complicated food prep.

The Download: ocean-based carbon removal, and Musk’s untweeted trip to China

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Meta’s former CTO has a new $50 million project: ocean-based carbon removal

The news: A nonprofit formed by Mike Schroepfer, Meta’s former chief technology officer, has spun out a new organization aimed at speeding up research into ocean alkalinity enhancement—a potential way to use the seas to suck up and store away even more carbon dioxide. The Carbon to Sea Initiative will get $50 million over the next five years to pursue that goal.

How it works: Ocean alkalinity enhancement refers to various ways of adding alkaline substances, like olivine, basalt, or lime, into seawater. These basic materials bind with dissolved inorganic carbon dioxide in the water to form bicarbonates and carbonates, ions that can persist for tens of thousands of years in the ocean. As those CO2-depleted waters reach the surface, they can pull down additional carbon dioxide from the air to return to a state of equilibrium. 

Why it matters: While such projects would be challenging to scale, climate modelers are optimistic about the method’s potential. Read the full story.

—James Temple

Elon Musk’s quiet, untweeted China trip

Ever since China lifted most of its pandemic-era travel restrictions in January, foreign executives have been flocking in—including one Elon Musk. He paid a three-day visit to China last week to meet with high-ranking government officials. Unusually for him, he stayed off Twitter the entire time. 

However, from the public readouts posted by Chinese government websites and sightings of Musk shared on Chinese social media, we can reconstruct his trip. Read the full story.

—Zeyi Yang

Zeyi’s story is from China Report, his weekly newsletter giving you the inside track on all things tech in China. Sign up to receive it in your inbox every Tuesday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The US regulator is suing Coinbase, too
Within 24 hours of going after fellow crypto exchange Binance. (WSJ $)
+ Retail crypto trading in the US isn’t looking so rosy right now. (Wired $)

2 OpenAI has no plans to launch any more products 

CEO Sam Altman says ChatGPT will be the last. (Insider $)+ The inside story of how ChatGPT was built from the people who made it. (MIT Technology Review)

3 Headsets are out, goggles are in
Apple is going all in on mixed reality—just don’t mention the metaverse. (The Atlantic $)
+ Wearing a computer on your face is still a weird experience. (Wired $)
+ Apple will need to convince developers to build apps for its headset. (MIT Technology Review)

4 Conservative activists are pressuring disinformation researchers
The unwanted attention is forcing some researchers out of the field, just as the 2024 US election approaches. (WP $)

5 The European Union may ban Huawei from 5G infrastructure
The bloc worries that its members haven’t heeded its warnings about high risk vendors. (FT $)

6 Johnson & Johnson’s covid vaccine has been withdrawn in the US
A lack of demand for the jab means there’s no need to update it. (Ars Technica)

7 A startup placed a brain implant on patients’ skulls for 15 minutes
The flexible devices are much less invasive than traditional electrodes. (Wired $)
+ How your brain data could be used against you. (MIT Technology Review)

8 How a hospital staffing startup imploded
CareRev’s CEO openly discussed his drug use with colleagues, for starters. (The Information $)

9 Finland is raising a generation of fact-checkers
It’s the global gold standard for teaching media literacy to children. (Slate $)
+ How different generations handle misinformation. (MIT Technology Review)

10 We’re finally learning more about synesthesia 🎨
Scientists now believe it’s closely linked to how we learn as children. (New Scientist $)

Quote of the day

“People hand out 5 stars like it’s candy.”

—Uber driver Donnie Freeman believes passengers are almost over-generous with ratings these days, he tells the Wall Street Journal.

The big story

The uneasy coexistence of Yandex and the Kremlin

August 2020

While Moscow was under coronavirus lockdown between March and June 2020, the Russian capital emptied out—apart from the streams of cyclists in the trademark yellow uniform of Yandex’s food delivery service.

Often referred to in the West as Russia’s Google, Yandex is really more like Google, Amazon, Uber, and maybe a few other companies combined. It’s a Russian Silicon Valley unto itself. 

But Yandex’s success has come at a price. The Kremlin has long viewed the internet as a battlefield in its escalating tensions with the West and has become increasingly concerned that a company like Yandex, with the heaps of data it has on Russian citizens, could one day fall into foreign hands. Read the full story.

—Evan Gershkovich

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Aww, Banana the lobster has made a friend.+ I must admit, putting butter in porridge is a new one on me.
+ Archaeologists have uncovered bits and pieces of a Medieval church buried beneath the North Sea.
+ Oh I do like to be beside the seaside—reading about the seaside, too.
+ Want to see the world through the eyes of the Roman Empire? Now you can.

Google DeepMind’s game-playing AI just found another way to make code faster

DeepMind’s run of discoveries in fundamental computer science continues. Last year the company used a version of its game-playing AI AlphaZero to find new ways to speed up the calculation of a crucial piece of math at the heart of many different kinds of code, beating a 50-year-old record.

Now it has pulled the same trick again—twice. Using a new version of AlphaZero called AlphaDev, the UK-based firm (recently renamed Google DeepMind after a merge with its sister company’s AI lab in April) has discovered a way to sort items in a list up to 70% faster than the best existing method.

It has also found a way to speed up a key algorithm used in cryptography by 30%. These algorithms are among the most common building blocks in software. Small speed-ups can make a huge difference, cutting costs and saving energy.

“Moore’s Law is coming to an end, where chips are approaching their fundamental physical limits,” says Daniel Mankowitz, a research scientist at Google DeepMind. “We need to find new and innovative ways of optimizing computing.”

“It’s an interesting new approach,” says Peter Sanders, who studies the design and implementation of efficient algorithms at the Karlsruhe Institute of Technology in Germany and who was not involved in the work. “Sorting is still one of the most widely used subroutines in computing,” he says.

DeepMind published its results in Nature today. But the techniques that AlphaDev discovered are already being used by millions of software developers. In January 2022, DeepMind submitted its new sorting algorithms to the organization that manages C++, one of the most popular programming languages in the world, and after two months of rigorous independent vetting, AlphaDev’s algorithms were added to the language. This was the first change to C++’s sorting algorithms in more than a decade and the first update ever to involve an algorithm discovered using AI.

DeepMind added its other new algorithms to Abseil, an open-source collection of prewritten C++ algorithms that can be used by anybody coding with C++. These cryptography algorithms compute numbers called hashes that can be used as unique IDs for any kind of data. DeepMind estimates that its new algorithms are now being used trillions of times a day.

AlphaDev is built on top of AlphaZero, the reinforcement-learning model that DeepMind trained to master games such as Go and chess. DeepMind’s breakthrough was to treat the problem of finding a faster algorithm as a game and then get its AI to win it—the same method it used to speed up calculations in last year’s research.

In AlphaDev’s case, the game involves choosing computer instructions and placing them in order so that the resulting lines of code make up an algorithm. AlphaDev wins the game if the algorithm is both correct and faster than existing ones. It sounds simple, but to play well, AlphaDev must search through an astronomical number of possible moves.  

DeepMind chose to work with assembly, a programming language that can be used to give specific instructions for how to move numbers around on a computer chip. Few humans write in assembly; it is the language that code written in languages like C++ gets translated into before it is run. The advantage of assembly is that it allows algorithms to be broken down into fine-grained steps—a good starting point if you’re looking for shortcuts.

Computer chips have different slots where numbers get put and processed. Assembly includes basic instructions for manipulating what’s in these slots, like mov(A,B), which tells a computer to move the number that’s in slot A to slot B, and cmp(A,B), which tells the computer to check if what’s in slot A is less than, equal to, or greater than what’s in slot B. Long sequences of such instructions can carry out everything that computers do.

AlphaDev plays a move in the game by adding a new assembly instruction to the algorithm it is building. To start, AlphaDev would add instructions at random, generating algorithms that would not run. Over time, just as AlphaZero did with board games, it learned to play winning moves. It added instructions that led to algorithms that not only ran, but were correct and fast.

DeepMind focused on algorithms for sorting short lists of three to five items. Such algorithms get called over and over again in programs that sort longer lists. Speed-ups in these short algorithms will therefore have a cumulative knock-on effect.

But short algorithms have also been studied and optimized by humans for decades. Mankowitz and his colleagues started with an algorithm for sorting a list of three items just as a proof of concept. The best human-devised version of this algorithm involves 18 instructions. They didn’t believe they’d be able to improve on it.

“We honestly didn’t expect to achieve anything better,” he says. “But to our surprise, we managed to make it faster. We initially thought this was a mistake or a bug or something, but when we analyzed the program we realized that AlphaDev had actually discovered something.”

AlphaDev found a way to sort a list of three items in 17 instructions instead of 18. What it had discovered was that certain steps could be skipped. “When we looked at it afterwards, we were like, ‘Wow, that definitely makes sense,’” says Mankowitz. “But to discover something like this [without AlphaDev], it requires people that are experts in assembly language.”

AlphaDev could not beat the best human version of the algorithm for sorting a list of four items, which takes 28 instructions. But it beat the best human version for five items, cutting the number of instructions down from 46 to 42. 

That amounts to a significant speed-up. The existing C++ algorithm for sorting a list of five items took around 6.91 nanoseconds on a typical Intel Skylake chip. AlphaDev’s took 2.01 nanoseconds, around 70% faster. 

DeepMind compares AlphaDev’s discovery to one of AlphaGo’s weird but winning moves in its Go match against grandmaster Lee Sedol in 2016. “All the experts looked at this move and said, ‘This isn’t the right thing to do. This is a poor move,’” says Mankowitz. “But actually it was the right move, and AlphaGo ended up not just winning the game but also influencing the strategies that professional Go players started using.”

Sanders is impressed, but he does not think the results should be oversold. “I agree that machine-learning techniques are increasingly a game-changer in programming, and everybody is expecting that AIs will soon be able to invent new, better algorithms,” he says. “But we are not quite there yet.”

For one thing, Sanders points out that AlphaDev only uses a subset of the instructions available in assembly. Many existing sorting algorithms use instructions that AlphaDev did not try, he says. This makes it harder to compare AlphaDev with the best rival approaches.

It’s true that AlphaDev has its limits. The longest algorithm it produced was 130 instructions long, for sorting a list of up to five items. At each step, AlphaDev picked from 297 possible assembly instructions (out of many more). “Beyond 297 instructions and assembly games of more than 130 instructions long, learning became slow,” says Mankowitz.

That’s because even with 297 instructions (or game moves), the number of possible algorithms AlphaDev could construct is larger than the possible number of games in chess (10120) and the number of atoms in the universe (around 1080).

For longer algorithms, the team plans to adapt AlphaDev to work with C++ instructions instead of assembly. With less fine-grained control AlphaDev might miss certain shortcuts, but the approach would be applicable to a wider range of algorithms.

Sanders would also like to see a more exhaustive comparison with the best human-devised approaches, especially for longer algorithms. DeepMind says that’s part of its plan. Mankowitz wants to combine AlphaDev with the best human-devised methods, getting the AI to build on human intuition rather than starting from scratch.

After all, there may be more speed-ups to be found. “For a human to do this, it requires significant expertise and a huge amount of hours—maybe days, maybe weeks—to look through these programs and identify improvements,” says Mankowitz. “As a result, it hasn’t been attempted before.”

5 Content Marketing Ideas for July 2023

Search engine optimizers sometimes refer to content marketing as a hamster wheel: It needs nonstop generating to keep traffic flowing and visitors engaged.

In July 2023, there are many topics to keep the wheel turning. These include national holidays — Canada Day on July 1 and U.S. Independence Day on July 4 — and unconventional selections such as co-hosting a podcast with an AI tool.

Content marketing is the act of creating, distributing, and promoting articles, videos, and the like to attract, engage, and retain customers. What follows are five content topics your business can use in July 2023.

Amazon Prime Day

At the time of writing, Amazon had not yet announced the dates for Prime Day, its annual sales event. But if history holds, the sale should happen sometime in July.

Image of two girls laughing while pushing a shopping cart down a streetImage of two girls laughing while pushing a shopping cart down a street

Amazon Prime Day is a content marketing opportunity even if you don’t sell on that marketplace. Image: Joel Mott.

How your business uses content marketing should depend on whether it sells on the Amazon Marketplace.

For Amazon sellers, the content might feature Prime Day buying guides, podcasts discussing how your business prepares for Prime Day, or even product origin stories describing how your company developed its best-selling item.

Businesses that don’t sell on Amazon could address alternative shopping ideas, such as “The Best Products You Can’t Find on Amazon” or “Sustainability: Why the Store You Shop Matters.”

Elvis Presley

Photo of Elvis PresleyPhoto of Elvis Presley

Elvis Presley in 1958, as his career was gaining momentum. Photo: Wikimedia Commons.

On July 5, 1954, Elvis Presley recorded his breakthrough hit “That’s All Right,” marking the start of his legendary music career.

Your company can tap into nostalgia and Presley’s cultural significance to create compelling content that resonates with your audience.

Here the key to content success is finding unique ways to connect your products or industry to Elvis or the music industry.

Blog titles could include:

  • “The King’s Influence: How Elvis Shaped the Fashion Industry”
  • “Rock and Roll Decor: Elvis-inspired Interior Design Ideas”
  • “Elvis-inspired Playlist: Music to Get Your Workout All Shook Up”

Imagine a company such as Gymshark (apparel) or Onnit (supplements) using that last idea.

National Mojito Day

Photo of a mojito drink on an outdoor tablePhoto of a mojito drink on an outdoor table

The mojito is a popular summertime cocktail with Cuban origins. Photo: Gabriel Petry.

July 11 is National Mojito Day, an occasion to create content that celebrates this refreshing cocktail or the ideas it embodies.

The mojito cocktail has a rich history rooted in Cuban culture and can be traced to the 16th century when Spanish explorers and settlers arrived on the island. The original version of the mojito was called “El Draque” after Sir Francis Drake, an English pirate who sailed the Caribbean. Legend has it that Drake’s crew consumed a mixture of aguardiente (a crude form of rum), sugar, lime, and mint leaves to cure various ailments and boost their spirits.

Over time, the recipe evolved to include rum, mint, lime juice, sugar, and soda water, resulting in today’s classic mojito.

National Mojito Day offers content marketers the opportunity to address the cocktail and any summer activity with a “mojito” vibe.

Here are examples for men’s apparel shops:

  • “Dressing Up Your Mojito: Stylish Attire for Summer Cocktail Parties”
  • “Mojito Nights: How to Look Sharp at Rooftop Bar Gatherings”
  • “The Perfect Mojito Date: Outfit Ideas for a Night Out”
  • “From Office to Mojito Hour: Transitioning Your Look for After-work Drinks”
  • “Mojito Vibes: Summer Suiting Tips for an Effortlessly Cool Look”

AI Co-host

This content marketing idea embraces the artificial intelligence boon.

First, consider launching a podcast for your business. Then add a twist, use an AI tool as your co-host.

Armando: Would you like to co-host a podcast with me?

ChatGPT: OMG, like, totally! That sounds absolutely amazing! I'm, like, super excited to be your co-host 
for a national podcast. We can talk about all the cool stuff that teens love, like fashion, music,
movies, celebrity gossip, and so much more. We'll have the best time ever, sharing our
thoughts, interviewing cool guests, and spreading positive vibes to all our listeners. It's going
to be, like, a dream come true! Let's make this podcast the talk of the town, girl!

Pick a topic relevant to your industry and the products you sell that will likely attract, engage, and retain customers. For example, a brand such as Lmnt (athletic drinks) might develop a fitness podcast covering workouts, mountain biking, or sunbathing.

Then ask the AI tool a question. You can read those answers or use a text-to-speech service to give the AI a voice in the podcast.

Independence Days

Photo of nighttime fireworks in the skyPhoto of nighttime fireworks in the sky

Fireworks are a staple of Independence Day celebrations. Photo: Jeffery Hamilton.

I’ve saved a top idea for the end. July 1 is Canada Day, and July 4 is America’s Independence Day.

These dates are among the most important sales opportunities for North American retail businesses. Consider creating articles or videos highlighting the history, traditions, and festivities associated with these holidays. As always, find ways to connect the content to your products.

Google Cloud Introduces Generative AI Support In Vertex AI via @sejournal, @MattGSouthern

Google is rolling out an update to its cloud-based machine learning platform, Vertex AI, which brings support for generative capabilities.

This addition makes making advanced generative AI models accessible to individuals and businesses beyond the realm of data science and engineering.

Enabling Access To Advanced Generative AI Models

Generative AI support on Vertex AI provides users access to Google’s extensive generative AI models.

These models cover various content types, including text and chat, images, code, and text embeddings.

Vertex AI allows you to select the one that best suits specific use cases by categorizing the models based on their content generation capabilities.

One of the notable generative AI models is PaLM 2, a language model that drives the PaLM API.

PaLM 2 boasts improved multilingual, reasoning, and coding capabilities, empowering users to tackle language-based tasks more efficiently and accurately.

Leveraging The Power Of PaLM API

Vertex AI enables users to leverage the generative capabilities of Google’s PaLM API.

This API, powered by large language models (LLMs), generates text and code in response to natural language prompts.

It offers specialized features tailored to different use cases, which include the following:

  • The PaLM API for text is fine-tuned to excel in language tasks.
  • The PaLM API for chat is designed for multi-turn conversations.
  • The Text Embedding API generates vector embeddings for input text.
  • The Codey APIs include models for code generation, code completion suggestions, and code-related questions.

Democratizing AI: Accessibility & Simplicity

By adding generative capabilities to Vertex AI, Google aims to democratize the technology by making it available to more people.

The platform offers an intuitive interface, including Generative AI Studio, that you can use without extensive technical knowledge.

Generative AI Studio focuses on low-code implementation. This means that Google’s multimodal foundation models, including PaLM, Imagen, Codey, and Chirp, can be integrated into applications with a few lines of code.

Developers, even those without a background in machine learning, can leverage this technology without worrying about the complexities of provisioning storage and compute resources.

Cost-Effectiveness & Flexibility

While using Vertex AI involves costs, Google Cloud offers various pricing options and flexibility to accommodate different user needs.

This ensures that individuals or small businesses with limited resources won’t have substantial upfront investments.

In Summary

Google’s latest update to Vertex AI democratizes artificial intelligence by offering accessible and advanced generative models to a broader audience.

With its intuitive, low-code Generative AI Studio, the platform removes the technical barriers associated with AI, encouraging even non-tech-savvy individuals to take advantage of it.

Source: Google

Featured Image: Tada Images/Shutterstock

Google Enhances Bard’s Reasoning Skills via @sejournal, @MattGSouthern

Google’s language model, Bard, is receiving a significant update today that aims to improve its logic and reasoning capabilities.

Jack Krawczyk, the Product Lead for Bard, and Amarnag Subramanya, the Vice President of Engineering for Bard, announced in a blog post.

A Leap Forward In Reasoning & Math

These updates aim to improve Bard’s ability to tackle mathematical tasks, answer coding questions, and handle string manipulation prompts.

To achieve this, the developers incorporate “implicit code execution.” This new method allows Bard to detect computational prompts and run code in the background, enabling it to respond more accurately to complex tasks.

“As a result, it can respond more accurately to mathematical tasks, coding questions and string manipulation prompts,” the Google team shared in the announcement.

System 1 and System 2 Thinking: A Blend of Intuition and Logic

The approach used in the update takes inspiration from the well-studied dichotomy in human intelligence, as covered in Daniel Kahneman’s book, “Thinking, Fast and Slow.”

The concept of “System 1” and “System 2” thinking is central to Bard’s improved capabilities.

System 1 is fast, intuitive, and effortless, akin to a jazz musician improvising on the spot.

System 2, however, is slow, deliberate, and effortful, comparable to carrying out long division or learning to play an instrument.

Large Language Models (LLMs), such as Bard, have typically operated under System 1, generating text quickly but without deep thought.

Traditional computation aligns more with System 2, being formulaic and inflexible yet capable of producing impressive results when correctly executed.

“LLMs can be thought of as operating purely under System 1 — producing text quickly but without deep thought,” according to the blog post. However, “with this latest update, we’ve combined the capabilities of both LLMs (System 1) and traditional code (System 2) to help improve accuracy in Bard’s responses.”

A Step Closer To Improved AI Capabilities

The new updates represent a significant step forward in the AI language model field, enhancing Bard’s capabilities to provide more accurate responses.

However, the team acknowledges that there’s still room for improvement:

“Even with these improvements, Bard won’t always get it right… this improved ability to respond with structured, logic-driven capabilities is an important step toward making Bard even more helpful.”

While the improvements are noteworthy, they present potential limitations and challenges.

It’s plausible that Bard may not always generate the correct code or include the executed code in its response.

There could also be scenarios where Bard might not generate code at all. Further, the effectiveness of the “implicit code execution” could depend on the complexity of the task.

In Summary

As Bard integrates more advanced reasoning capabilities, users can look forward to more accurate, helpful, and intuitive AI assistance.

However, all AI technology has limitations and drawbacks.

As with any tool, consider approaching it with a balanced perspective, understanding the capabilities and challenges.

Featured Image: Amir Sajjad/Shutterstock

Microsoft Advertising Boosts Analytics & Global Reach In June Update via @sejournal, @MattGSouthern

Microsoft Advertising details several important updates and expansions in its June product roundup.

The new tools and features aim to enhance website performance analytics, improve cross-device conversion tracking, expand into new global markets, and integrate more seamlessly with other platforms.

Introducing Universal Event Tracking Insights

This month’s standout news is the introduction of Universal Event Tracking (UET) insights, a feature that gives advertisers a deeper understanding of their website’s performance.

The new feature requires no additional coding and will enhance the capabilities of existing UET tags.

“We’re introducing UET insights, a valuable new feature that we’ll add to your existing UET tags with no additional coding required from you. You’ll get a deeper understanding of your website’s performance and also enable Microsoft Advertising to optimize your ad performance more effectively via improved targeting, fraud detection, and reduced conversion loss.”

The new insights tool will roll out automatically starting July 3.

Cross-Device Conversion Attribution Update

Microsoft Advertising is introducing a cross-device attribution model later this month.

This update will enable advertisers to track and connect customers’ conversion journeys across multiple devices and sessions.

Microsoft explains the new feature in a blog article: “For example, if a user clicks on an ad using their laptop but converts on their phone, we’ll now credit that conversion to the initial ad click on the laptop.”

While the update doesn’t introduce new features or settings, advertisers may notice a slight increase in the number of conversions due to improved accuracy.

Expanding to New Markets

In line with its expansion push throughout 2022, Microsoft Advertising announces it’s expanding its advertising reach to 23 new markets.

The new additions include diverse locations ranging from Antigua and Barbuda to Wallis and Futuna.

This expansion allows advertisers to reach their audiences in more parts of the world.

Seamless Integration With Pinterest & Dynamic Remarketing

Microsoft Advertising is releasing Pinterest Import in all markets via the Microsoft Audience Network (MSAN), allowing advertisers to import campaigns from Pinterest Ads.

Further, Dynamic remarketing on MSAN for Autos, Events & Travel is now available in the US, Canada, and the UK.

The remarketing tool enables advertisers to use their feeds to create rich ad experiences on the Microsoft Audience Network and match their target audience with items in their feed where they’ve shown interest.

In Summary

Key takeaways from the June product roundup include the automatic rollout of UET Insights starting July 3, introducing a new cross-device attribution model, expanding into 23 new global markets, and enhanced integration with Pinterest via the Microsoft Audience Network.

These developments collectively offer advertisers increased insight into campaign performance, improved accuracy in conversion tracking, and more opportunities to reach audiences worldwide.

Source: Microsoft
Featured Image: PixieMe/Shutterstock

WordPress Now Has An AI Content Generator – Free Access Available via @sejournal, @martinibuster

Jetpack unveiled a new WordPress plugin that integrates AI directly into the WordPress editor, allowing publishers to generate content within the WordPress publishing workflow.

Jetpack by Automattic

Automattic is a software development company that is behind many widely used plugins, software and websites, like WooCommerce, WordPress.com, Tumblr, Akismet and Jetpack.

Founded by Matt Mullenweg, the developer and founder of WordPress, Automattic contributes to many open source projects like WordPress, WordCamp US, and bbPress.

Although Automattic is a wholly separate company from the non-profit WordPress.org, the expertise from developing for and contributing to the WordPress makes Automattic software the gold standard for plugins.

Jetpack AI Assistant

Jetpack took the wraps off a new plugin called Jetpack AI Assistant to serve as a writing assistant for publishers.

The plugin makes the AI assistant available within the WordPress editor block within a chat-like interface, what is known as a conversational user interface.

That means you basically just write what you want in a conversational manner, like texting a person.

If you’re already familiar with ChatGPT then using the Jetpack AI content generator will be familiar.

The process of telling the AI what you want is referred to as writing a “prompt.”

If the resulting content needs editing, tell it to rewrite it with whatever you feel is missing from the content.

Video showing the conversational user interface:

Jetpack AI Assistant Interface

The AI Assistant is contained within the block editing interface.

WordPress AI user interface

WordPress Now Has An AI Content Generator – Free Access Available

Here’s a video showing how it’s selected:

Adaptive Writing Tones

The AI content generator has selectable writing tones that it calls Adaptive Tones that changes the writing style.

These are the writing tone options:

  • Formal
  • Informal
  • Optimistic
  • Humorous
  • Serious
  • Skeptical
  • Empathetic
  • Confident
  • Passionate
  • Provocative

Video Demonstrating Adaptive Tone

Title & Summary Generation

Creating titles and summaries are a bit of a pain. Jetpack’s AI plugin handles these writing chores.

Content Translation

Content translation works by choosing the translation option and selecting the language. The content that is on the editor automatically translates to the new language.

Spelling and Grammar Correction

Another great feature is the ability to automatically go through the document and correct spelling and grammar.

Video Showing Spelling & Grammar Correction

How Much Does WordPress AI Content Generator Cost?

There are 20 free requests available and thereafter it costs $20 per month for users of the WordPress CMS.

Those who use WordPress.com get it for free.

These prices are not set in stone. The announcement states:

“Give the Jetpack AI Assistant block a whirl! It’s ready for you to explore, with 20 free requests on us. After that, it’s just $10 per month.

Also, exciting news for WordPress.com users — the Jetpack AI Assistant is available free of charge on all WordPress.com sites for a limited time. Note that Jetpack AI is an experimental feature, so pricing may change in the future.”

If all you need is a solution for generating content for WordPress, then using the Jetpack AI plugin makes sense, especially considering that the content generation happens within the WordPress editing workflow. No cutting and pasting from one app to another.

The cost of the WordPress content generator plugin is half the price of ChatGPT, $10 per month, currently with no upper limits on requests.

The free version of the Jetpack plugin allows up to twenty free requests, with all features available for use. Thereafter users must upgrade to make more requests.

Upgrading to the paid version unlocks high volume requests and priority support.

At this time there is no upper limit to the amount of requests that can be made using the paid version.

Read the announcement of the new plugin:

Meet Your New Creative Writing Partner — The Jetpack AI Assistant

Featured image by Shutterstock/san4ezz