Big tech companies from Alphabet to Baidu are accelerating the integration of generative artificial intelligence – a technology that has gained popularity for its ability to generate human-like responses to text queries – into their offerings.

Microsoft announced that its line of business intelligence and application development tools within the Power Platform, including Power Virtual Agent and AI Builder, has been updated with the new capabilities.

The Power Virtual Agent chatbot creation tool can now connect to a company’s internal resources to generate weekly report summaries and customer inquiries.

Microsoft has also added generative artificial intelligence capabilities to AI Builder, which allows enterprises to automate workflows, and released a new version of its Dynamics 365 business management platform based on the technology.

Dynamics 365 Copilot is the latest version of Microsoft’s tool and includes a number of sales, customer service and marketing applications, integrates AI to automate certain tasks, such as collecting and analysing data or creating an email campaign, among other capabilities.

So far, the company has announced AI updates for its popular Windows operating system and Bing search engine, but not yet for the Office productivity suite, which includes Word and Excel.

This week, the world’s biggest search engine companies entered the race to use a powerful new breed of “generative artificial intelligence” algorithms.

Most notably, Microsoft announced that it is repurposing Bing, which trails Google in popularity, to use ChatGPT, the insanely popular and often surprisingly capable chatbot created by artificial intelligence startup OpenAI, Wired wrote on the topic.

The all-new Bing is equally conversational. Demonstrations the company did at its Redmond headquarters and a quick test drive by WIRED’s Aarian Marshall, who attended the event, show that it can effortlessly generate a vacation itinerary, summarize highlights from product reviews, and answer complex questions, such as whether a piece of furniture will fit in a particular car.

It’s a far cry from Microsoft’s helpless and hopeless Office Clippy assistant, which some readers may recall bothering them every time they create a new document.

Not to be outdone by Bing’s artificial intelligence reboot, Google said this week that it will launch a competitor to ChatGPT called Bard. (The name was chosen to reflect the creative nature of the algorithm that lies beneath it, says one Google employee.)

The company, like Microsoft, has shown how the underlying technology can answer some Web searches and said it will start making the artificial intelligence behind the chatbot available to developers.

Last but not least in the new AI search wars is Baidu, China’s largest online search engine company. It joined the fray by announcing another ChatGPT competitor, Wenxin Yiyan (文心一言), or “Ernie Bot” in English. Baidu says it will release the bot to the market after the completion of internal tests in March this year.

These issues could be a problem if you’re trying to use technology to make web search more useful. Microsoft has apparently fixed some common flaws with ChatGPT in Bing, but the real test will come when it becomes widely available. One of Bard’s responses, which Google proudly boasts about, incorrectly claims that the James Webb Space Telescope was the first to take a picture of a planet outside our solar system.

The only exception where the programming language is not used as much is embedded systems (safety critical), as Python is dynamically typed and too slow. This is why C and C++ are currently gaining popularity. Looking at the rest of the TIOBE index, not much has happened in the last month.

Swift and PHP swapped places again at position 10, Rust moved closer to the Top 20, Kotlin returned to the top 30, and Google’s new language Carbon entered the TIOBE index at position 192. – Paul Jansen, CEO of TIOBE Software.

The TIOBE Programming Community Index is an indicator of the popularity of programming languages. The index is updated once a month. Rankings are based on the number of qualified engineers worldwide, courses and vendors. It is important to note that the TIOBE index is not about the best programming language or the language in which the most lines of code are written.

The index can be used to test programming skills or to make a strategic decision about what language to use when starting to build a new software system.

Apollo Go, Baidu’s robotaxi service, aims to be in 65 cities by 2025 and 100 cities by 2030.

Baidu has so far racked up over 16 million kilometers (10 million miles) of L4, self-driven distance, in terms of improving its driving tech.  That’s up from 6.2 million miles reported in its first-quarter results.

These enormous figures have limited substance unless we know how many of these rides actually happen on busy city roads rather than designated routes in enclosed areas.

Now in his latest venture, Landing AI, he is exploring how businesses without giant data sets to draw on can still join in the AI revolution. Ng joined MIT Technology Review’s virtual EmTech Digital annual AI event, to share the lessons he’s learned.

Andrew started by explaining that in terms of how he executes the business, he tends to be customer-led or mission-led, and almost never technology-led.

He shared that after heading the AI teams at Google and Baidu, he realized that AI has transformed software consumer internet. However, Ng wanted to take AI to all of the other industries, which is an even bigger part of the economy, so he decided to focus on manufacturing. According to Andrew, one huge difference in consumer software internet is the fact that there we have a billion users and a huge amount of data. But he pointed out that in manufacturing, no factory has manufactured a billion or even a million scratched smartphones. Hence the challenge is, can we get an AI to work with a hundred images… Well, in his opinion “it often turns out we can.”

For Andrew, machine learning is so diverse that it’s becoming really hard to give one-size-fits-all answers.

He thinks that today building AI systems are still very manual. There are a few brilliant machine-learning engineers and data scientists who do things on a computer and then push things to production. There’s a lot of manual steps in the process.

He also pointed out that if we look at a lot of the typical business problems there’s a lot of room for automation and efficiency improvement. Andrew hopes that the AI community can look at the biggest social problems too – eg. climate change, homelessness or poverty. He added:

“It’s more important to start quickly, and it’s okay to start small. My first meaningful business application at Google was speech recognition, not web search or advertising. But by helping the Google speech team make speech recognition more accurate, that gave the Brain team the credibility and the wherewithal to go after bigger and bigger partnerships. So Google Maps was the second big partnership where we used computer vision—to read house numbers to geolocate houses on Google maps. And only after those first two successful projects did I have a more serious conversation with the advertising team. So I think I see more companies fail by starting too big than fail by starting too small. It’s fine to do a smaller project to get started as an organization to learn what it feels like to use AI, and then go on to build bigger successes.”

Ng recommended that if our company isn’t already making pretty aggressive and smart investments, this is a good time because AI is causing a shift in the dynamics of many industries.