Tinder’s verification process will now use AI and video selfies Sarah Perez @sarahintampa / 18 hours
Tinder today is rolling out an AI-powered update to its Photo Verification feature, which to date has allowed the app’s users to prove to others they’re neither a bot nor a catfisher. In the past, users would take pictures of themselves, posing as instructed, to become verified on the dating app and receive a blue check. Now, Tinder is strengthening this process by requiring a video selfie instead of photos. Plus, it will soon allow users to restrict their chats to only those members who are also Photo Verified.
The company says the changes are a part of Tinder’s work to make the app safer for its members.
However, the feature also arrives at a time when it’s become much easier to leverage AI tools to create fake photos and personas, which could fill dating apps with fake people who are really just bots poised to spam their matches. Requiring a “liveness” check, as a video selfie does, is a much stronger means of vetting that people are who they say they are and weeding out spammers.
Tinder says it’s working with a third-party partner to manage the video selfie verification process, rather than running it in-house, but declined to name the vendor.
However, it explains that the new model will first require the user to complete a series of video prompts, which the AI then uses to match that the person in the video also matches the person in the profile photo the user wants to verify. The integration works by matching a 3D mapping of someone’s likeness (their facial geometry) to their still photo.
As the updates roll out, starting on Wednesday, users who aim to be Photo Verified or who want to maintain their existing verification will have to take a video selfie. The feature will fully replace the prior option to upload photos.
Existing Photo Verified will soon begin to receive prompts in the app to upgrade to the latest version of Photo Verification if they want to keep their blue checkmarks on Tinder, the company notes. This not only ensures that members get verified through the more robust video selfie feature but also addresses the problem of lapsed Tinder users returning to the app where their verified photos are now years old.
In addition to updating the feature to use videos instead of photos, Tinder will later introduce new features that allow users to only see other Photo Verified members in their recommendations, via their Message Settings. And it will allow members to ask their Matches to Photo Verify before they’re allowed to send a message. (It’s hard to imagine how this will make for a nice first impression, though!)
Tinder Gold subscribers, meanwhile, will be able to filter their “Likes” page for Photo Verified members only.
The company claims that Photo Verification has been proven to increase matches on the service, as users feel more assured that their potential match is a real person, not a bot — and that they look like their photos. Tinder says among its 18 to 25-year-old users, being Photo Verified gives them a 10% higher chance to match, for example.
The Photo Verification feature will roll out today to Tinder’s global users while the ability to restrict messages to “Photo Verified Members” only will arrive in the “coming months,” Tinder says.
TikTok is testing an in-app tool that creates generative AI avatars Aisha Malik 8 hours
TikTok is experimenting with a new tool that allows users to create generative AI avatars, the company confirmed to TechCrunch. The new tool was first spotted by social media consultant Matt Navarra. The tool isn’t broadly available, and is currently being tested in a few select markets, the company said. With this test product, TikTok is essentially building a Lensa-like app directly within its platform.
Once users get access to the tool, it will ask them to select between three to 10 photos to create avatars, according to screenshots posted by Navarra. You can only use the tool once a day, and each time you use it, it will generate up to 30 avatars.
TikTok has a NEW generative AI avatar creator! 🤖🎨📷
View thread to see what it can do 👇 pic.twitter.com/TDBbwok6bt
— Matt Navarra (@MattNavarra) April 25, 2023
After you upload your images, you can pick up to five different styles for the tool to use when generating your avatars. Navarra notes that it takes a couple of minutes for the app to generate the AI avatars. You can then choose to download one or several of the AI avatars. You have the option to share an avatar to your TikTok story or upload it as your profile avatar.
“We’re always thinking about new ways to add value to the community and enrich the TikTok experience, as we continue to build a safe place that entertains, inspires creativity, and drives culture,” a spokesperson for TikTok told TechCrunch in an email. “In a few select regions, we’re experimenting with a new way to create and share profile pictures with the TikTok community.”
Although the styles with TikTok’s tool are more limited than what you can get on Lensa, a paid app, the results are impressive.
And give you the option to share an avatar to your TikTok story and / upload it as your profile avatar pic.twitter.com/XPzhNxjqsK
— Matt Navarra (@MattNavarra) April 25, 2023
Photos that violate TikTok’s Community Guidelines cannot be used to create avatars, and photos that are uploaded will be moderated by the app’s content moderation systems. TikTok will delete all of the photos that users upload after a short period of time.
TikTok says that the features it experiments with don’t always end up in the final product, and for features that do, they can look and feel different by the time they launch broadly.
Last winter, Lensa climbed to the top of the U.S. App Store charts as users around the world posted artistic renditions of themselves that they generated on the app. In response to the app’s success, consumer demand for AI edits had pushed numerous other “AI” apps into the U.S. App Store’s Top Charts. At the time, the top three spots on the U.S. App Store were all held by AI photo editors.
Given the success around generative AI avatar tools, it’s no surprise that TikTok is looking to incorporate its own version within its platform. Of course, the success around AI photo apps is paired with controversy, as artists have raised red flags about apps like Lensa AI sampling their work. TikTok is likely looking to avoid such controversy by experimenting with a limited tool.
It’s worth noting that this isn’t the first time that TikTok has built and incorporated its own limited version of a popular AI app. Back in August 2022, the company introduced an in-app text-to-image AI generator that lets users type in a prompt and receive an image that can be used as the background in their videos. The filter was released in response to the popularity of OpenAI’s DALL-E 2 text-to-image AI generator.
TikTok rolls out a basic in-app, text-to-image AI generator
From DrakeGPT to Infinite Grimes, AI-generated music strikes a chord Amanda Silberling 7 hours
Last week, a song using AI deepfakes of Drake and the Weeknd’s voices went viral, but neither major artist was involved in its creation. Meanwhile, Grimes has taken to Twitter to offer 50% royalties on any AI-generated song that uses her voice, then declared that she is interested in “killing copyright,” which would probably undermine her ability to collect royalties in the first place. We might be living in the weirdest timeline, but unless Grimes is working on any secret inter-dimensional transit projects (you never know), the music industry has to reckon with what to do next.
Musicians like Holly Herndon and YACHT have embraced AI as a tool to push the limits of their creativity. YACHT trained an AI on 14 years of their music, then synthesized the results into the album “Chain Tripping;” Herndon created Holly+, a website that freely allows anyone to create deepfake music using her own voice.
While Herndon may openly invite people to experiment with AI art using her likeness, most artists don’t even know that people can model their voice before it’s too late. Therein lies the problem.
“The element that really needs to be centered is these questions of consent,” said Kevin Erickson, Director of the Future of Music Coalition, in a conversation with TechCrunch. “If we just decide because the technology is capable of bypassing everybody’s consent, that we’re just going to go along with it… that means that we’re not engaging with some of the most important and central questions about ethics, and some of the most central and important questions about labor.”
In Spotify’s recent quarterly earnings call, CEO Daniel Ek spoke about the company’s approach to AI-generated music. Despite Spotify taking down “Heart on my Sleeve,” the AI song that uses deepfakes of Drake and the Weeknd, Ek seems cautiously optimistic about the fast-developing technology.
“[AI] should lead to more music,” Ek said on the call. “More music, obviously, we think is great culturally.”
For a big business like Spotify, that might be true: if more people use their streaming service to listen to more music, then they get more money. But for many artists and music fans, AI poses a threat.
“When artists are already struggling, it seems like a dangerous step,” entertainment lawyer Henderson Cole told TechCrunch.
Between abysmal streaming payouts and the longterm impact of COVID-19 on the live music industry, musicians have been having a rough go of it, to say the least. Now, like visual artists, these performers have become guinea pigs for technology that appropriates their work without consent.
“Music has a special social role in the development of technology,” Erickson told TechCrunch. “It can be attached to any kind of emerging technology as a way of providing a use case or selling general interest and attracting investment.”
We saw this happen with the crypto industry, which at one point seemed poised to change the status quo of music royalties and ticketing, but has yet to reach anything close to mass adoption.
Sometimes these new technologies do take hold, though. As an historical example, Erickson points to sampling, or the practice of iterating on snippets of other artists’ work in new recordings. So long as a musician gets permission from the artist and their label, sampling is fair game.
“It was centered in community rather than the technology itself,” Erickson said about sampling. Of course, in cases where music was sampled without the artists’ consent, some high-profile lawsuits ensued. Now, it’s only a matter of time before we see rights holders get over AI-generated music.
Under certain circumstances, copyrighted material can be used without explicit permission if it is considered “fair use.” Fair use analysis considers whether a work was created for profit, the amount of copyrighted material it uses, how transformative it is and if it might economically impact the original.
Though a fair use argument could be constructed in favor of AI music, Cole thinks it’s doubtful that it would hold much weight in practice.
“In a world where Ed Sheeran and Robin Thicke are getting sued just for sounding similar to a hit song, someone using AI to copy an artists’ voice or musical sound seems unlikely to be allowed,” Cole said.
It takes a long time for the legal system to catch up with new technology, but for now, major labels like Universal Music Group (UMG) have spoken out in opposition to the use of generative AI.
“We have a moral and commercial responsibility to our artists to work to prevent the unauthorized use of their music and to stop platforms from ingesting content that violates the rights of artists and other creators,” a UMG representative said in a statement. The representative said that the rise of AI-generated music “begs the question as to which side of history all stakeholders in the music ecosystem want to be on: the side of artists, fans and human creative expression, or on the side of deep fakes, fraud and denying artists their due compensation.”
AI music generators could be a boon for artists — but also problematic
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Artificial intelligence and machine learning are changing how businesses operate. Enterprises are amassing a vast amount of data, which is being used within AI and ML models to automate and improve business processes. This in turn drives the development of next-generation, data-enabled applications that allow enterprises to gain new data-driven insights and improve business performance.
The impact of AI and ML on the enterprise extends to the software engineering organization, as applications that run the business will increasingly have AI and ML models embedded in them. Software engineering teams must therefore understand how these technologies will impact how they bring applications to market.
SEE: Business leaders’ expectations for AI/ML applications are too high, say chief data officers (TechRepublic)
AI and ML tools will fundamentally alter the ways in which applications are built – from design-to-code platforms and tools, to ML models that automatically generate code, to models that automate elements of application testing.
Many software engineers may believe the use of ML models in application development is just beginning to emerge, but that’s not the case. In a recent Gartner survey, almost 40% of software engineering organizations said they are already making moderate to extensive use of ML models in application development. However, most development teams do not have the level of understanding they should have about ML.
Here are three ways ML will impact software engineering and what developers need to know about this coming evolution.
Jump to:
ML-augmented application coding
ML-augmented application design
ML-augmented application testing
ML-augmented application coding
A new generation of coding assistants for professional developers is demonstrating not only longer and novel completions, but also the ability to use comments to generate code. ML-enabled code creation tools such as Copilot, CodeWhisperer and Tabnine plug into developers’ integrated development environment tools and generate application code automatically in response to a comment or a line of code. These code creation models are a derivative of the large language models that hyperscalers have been developing, such as OpenAI’s GPT-3.5, which is the basis of the ChatGPT application. For example, Codex is derived from GPT-3, but it has been optimized to create software code. Gartner predicts that by 2027, 50% of developers will use ML-powered coding tools, up from less than 5% today.
The question inevitably arises for software engineering leaders whether these models will eliminate or reduce the need for engineers who write application code. Current ML models that are designed to generate code will enhance developer productivity, but they will not replace developers in the near to medium term. However, the future may bring additional change.
ML-augmented application design
The impact of AI and ML on software engineering is not limited to embedding models in applications; it extends to the tools that designers are using to create compelling user experiences for their digital products. The workflow of transferring design assets and specifications from UX designers to software engineers is shown to be increasingly automated. The increasing adoption of design systems has helped to facilitate this transfer. These capabilities are expected to continue to improve rapidly, allowing for faster time to deployment of applications.
Historically, the different perspectives of designers and developers have caused problems in creating applications with a compelling UX. Looking to the future of digital product design in the enterprise, digital product team leaders will have both design and development skills. A “design strategist” role will emerge to lead converged teams of designers and developers to deliver better digital products quicker, while improving the quality of the applications.
ML-augmented application testing
AI and ML can also impact the application testing process in critical areas such as planning and prioritization, creation and maintenance, data generation, visual testing and defect analysis. Software engineering leaders face a shortage of experienced testers, especially people with the skills required to programmatically create tests. AI-augmented software-testing tools use algorithmic approaches to enhance tester productivity. This can dramatically increase the efficacy of test automation tools, enabling software engineering teams to improve software quality and reduce testing cycle times.
Several new vendors have entered the AI-augmented software-testing market, and vendor acquisitions were prevalent in the last year. Gartner predicts that by 2027, 80% of enterprises will have integrated AI-augmented testing tools into their software engineering toolchain, a significant increase from 10% in 2022. As applications become increasingly complex, AI-augmented testing will play a critical role in helping teams to deliver high-quality applications rapidly.
The impact of AI and ML on software engineering is significant, and the positive impact of the combined effort between data science and software engineering should not be underestimated. The wealth of data that the enterprise possesses can add significant value to business applications through models that generate forecasts, scoring models, next-best-action recommendations and other valuable business-enhancing tools. This joint effort can enable repeatable best practices that will improve enterprise performance and contribute to strong ROI for the expenditures the business is making in these technologies.
Van Baker. Image: Gartner
Van Baker is a vice president analyst at Gartner, Inc. covering cloud AI development services and generative AI including natural language, vision and automated machine learning services. Gartner analysts will provide additional insights on the latest application strategies at Gartner Application Innovation & Business Solutions Summit, taking place May 22–24, 2023 in Las Vegas, NV.
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TL;DR: Add the power of ChatGPT to your website with an extra $20 off this WordPress plugin, bringing the lifetime price down to just $39.97.
You might be a little rusty on your artificial intelligence knowledge, but that doesn’t mean you can’t leverage the power of AI in your business. While there are myriad business tools that use AI to help you reach positive outcomes, you might not have realized just how much you can harness OpenAI’s popular ChatGPT on your own website.
With the ChatGPT WordPress Plugin — rated 5/5 stars by verified purchasers — you can add the power of ChatGPT to your WordPress website in a matter of moments. Add it to your site, and then choose whether to make it available on the front end of your website, back end or both; you can even make it available only to logged-in users. That way, you can leverage a practically limitless set of possibilities for ChatGPT.
On the back end, you can use the plugin to generate content, complete tasks and perform keyword and topic research to inform future content offerings. On the front end, you can offer it to customers to get answers to their questions, navigate your website and more. The plugin also offers constant high-quality guidance to help you improve the ways you use ChatGPT and enhance your productivity.
Just remember you must have an OpenAI account to leverage that plugin, since it is tied to the ChatGPT version (free or Plus) that you’ve subscribed to through your account. But once you’re logged in, you’ll have a fully functional chatbot on your site.
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Amazon has added generative artificial intelligence models into Amazon Web Services. Generative AI is the type of artificial intelligence that can create text or images, similar to ChatGPT.
With Amazon Bedrock, customers can build and scale generative AI-based applications through an API. From there, the libraries of Amazon Titan FMs, which include two large language models, will be open as well as other models from AI21 Labs, Anthropic and Stability AI.
Amazon Bedrock is now available in limited preview.
Jump to:
What is Amazon Bedrock?
What are Amazon Titan FMs?
How will businesses use Amazon Bedrock?
Competition continues in the AI space
When will Amazon Bedrock be available, and how much will it cost?
What is Amazon Bedrock?
Amazon Bedrock is a service that provides access to generative AI on the cloud. Technically, Amazon Bedrock is a library of foundation models, all of which provide similar content-generating abilities. Since Amazon Bedrock’s models are hosted by AWS, existing clients can access them through their usual channels and not have to worry about hosting the model’s large amounts of data on their own infrastructure. However, enterprise clients will be able to feed data sets of their choice into the models.
Perhaps mindful of worries about security, Amazon reassured people that data fed into a training model in this way would not be used to train future iterations back at Amazon HQ.
Customers will also be able to use familiar AWS controls for the new AI. It connects to the cloud-based machine learning platform SageMaker ML, which includes an environment in which to test different models and a feature for managing foundation models at scale.
SEE: Looking to get started with the public version of ChatGPT?
What are Amazon Titan FMs?
While Amazon Bedrock is the service, Amazon Titan is the content. Amazon Titan offers two AI models: one that creates text and one that improves searches and personalizations. In addition to creating new text such as blog posts or emails, Amazon Titan can sort items into different classifications, hold open-ended conversations and extract specific information from chunks of text.
The latter enhances searches by tailoring the results to more relevant and contextual responses, Amazon said. A model similar to this one is already at work in Amazon’s product search.
How will businesses use Amazon Bedrock?
Once organizations have the AI hooked up to their existing AWS, Amazon said they can customize a model by feeding it just 20 examples of the kind of task that particular organization might want the AI to complete.
“We predict that most businesses’ long-term approach will be to customize large language models to their needs and data instead of out-of-the-box model usage,” a Slalom representative told Amazon.
Accenture, Deloitte, Infosys and Slalom are early integration partners.
Coda is one of the organizations using Amazon Bedrock in preview. “Since all our data is already on AWS, we are able to quickly incorporate generative AI using Bedrock, with all the security and privacy we need to protect our data built-in,” said Shishir Mehrotra, co-founder and CEO of Coda.
CodeWhisperer now includes free tier
Another possible use case specifically for developers comes from CodeWhisperer, an AI-based coding assistant. On Wednesday, Amazon announced CodeWhisperer now has a free tier. The no-cost Individual tier provides access to automated code-writing that lives inside a developer’s existing integrated development environment.
CodeWhisperer works well for “creating code for routine or time-consuming, undifferentiated tasks, working with unfamiliar APIs or SDKs, making correct and effective use of AWS APIs, and other common coding scenarios such as reading and writing files, image processing, writing unit tests,” Amazon wrote in a press release. A professional tier offers more features, such as SSO and IAM Identity Center integration and higher limits on security scanning.
Competition continues in the AI space
It’s hard not to see the AWS announcement as a response to OpenAI’s GPT-4, the generative AI service that became a household name with its public model, ChatGPT. In a blog post, Amazon reminds potential customers that AWS has been involved in the machine learning space for a long time: “AI and ML have been a focus for Amazon for over 20 years, and many of the capabilities customers use with Amazon are driven by ML.”
Amazon Bedrock’s major competitors are the enterprise subscription for ChatGPT (run by Microsoft and OpenAI) and Google’s PaLM model, which is also not yet available for enterprise customers.
When will Amazon Bedrock be available, and how much will it cost?
Amazon Bedrock is not currently available for new customers, and Amazon has not announced how much the service will cost. Visit Amazon’s Generative AI information page with an AWS account ID to sign up to learn when Bedrock will be more widely available.
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TL;DR: This AI-powered resume builder can show off the most impressive version of yourself and what you have to offer as a freelancer, consultant or B2B services provider, and a lifetime subscription is on sale for only $39.
Resumes are not just for employees anymore. If your business involves freelancing, consulting or even providing B2B services, potential clients will want to know all about you. And now you can show yourself and what you have to offer in the best possible light with a lifetime subscription to AI Resume Builder.
AI Resume Builder has an AI-powered resume writer that helps you create professional-looking resumes two times faster using drag-and-drop, templates, easy-to-use toggles and enhanced design controls. Of course, employees looking for positions will also love that the resumes are ATS-friendly. Best of all, it’s currently on sale for a best-on-web price of just $39.
Since you’re no one-trick pony, you’ll probably want to highlight different skills or services when contacting various companies. AI Resume Builder makes that a breeze, allowing you to create multiple resumes for a variety of job profiles, including different profile pictures if you wish.
The built-in AI engine auto-completes and fills in data for you, so you only have to enter it once. With just a few clicks, you can create customized sections that work just like the native sections in your resume. You can also add links to your social media accounts, including LinkedIn, Twitter, GitHub, Behance, Portfolio and others. Grammarly integration is supported as well.
Your resume can be adjusted to reflect your desired look. The drag-and-drop layout lets you easily arrange every element of your resume just the way you like it. Add your favorite color or convert one column into two with a single click. If you need a bit of extra room to fit in more content, simply alter the spacing.
AI Resume Builder’s Basic Plan offers an unlimited AI resume writer that allows you to create up to 10 resumes each month and download up to 50 of them. You’ll even get tips for improving your resume. It’s no wonder that AI Resume Builder got 127 Upvotes on Product Hunt.
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Microsoft’s Bing has long been a side note when it comes to search engines, languishing in relative obscurity, while Googling has been commonly used as a verb in casual conversation for decades. However, Microsoft partnering with OpenAI and pulling ahead in the generative AI race may make Bing more competitive, or at least make Google seriously consider its rival an innovator.
There has allegedly been some “panic” within Google around the subject of AI lately, according to documents reviewed by The New York Times. As a result, Google plans to integrate new AI features into search beginning next month for up to one million people in the U.S., the NYT article stated.
Jump to:
Microsoft adding AI to Bing made waves
How is Google responding to the Samsung/Bing news?
What changes may be coming to Google search?
Microsoft adding AI to Bing made waves
The first sign that Microsoft’s plan to add AI to Bing would signal a shift in the growing search AI industry came from Samsung, noted the NYT. In March 2023, the electronics titan reported there had been internal discussion about making Bing the default search engine on Samsung devices, according to the NYT.
The NYT notes that no information has come to light proving that Samsung considered changing its default search engine because of Microsoft’s AI announcement, though this idea is the prevailing rumor causing a sense of urgency within Google.
Microsoft has partnered with OpenAI to add natural language response capabilities to the version of Bing currently available in preview on the Edge browser. Microsoft’s AI copilot, built on one of OpenAI’s large language models, can summarize information or answer open-ended questions.
How is Google responding to the Samsung/Bing news?
According to The New York Times, Google quickly spun up “Project Magi,” a project in which more than 160 employees work in “sprint rooms” to edit and test the proposed AI-powered changes.
Internal memos acquired by The New York Times said some Google employees believed $3 billion in annual revenue was at stake if Samsung switched to Microsoft and dropped the existing Google search contract. It’s reported that Google has a similar contract with Apple, though it’s allegedly worth $20 billion and up for renewal this year. Google’s search engine business was worth $162 billion total last year.
Google’s plan to stay competitive is twofold: add AI to its existing search engine and create an entirely new search product. Updates to the existing search engine are likely to be the first priority, according to the NYT.
What changes may be coming to Google search?
The big idea is that Google search would be more personalized once AI comes into play; it would also host the ads that make up the bulk of Google’s revenue. (Bard, Google’s entry into the generative AI field, does not integrate ads into its answers.) The proposed improvements to Google search would allow users to ask follow-up questions, refining or correcting their search as needed, while the AI keeps track of what was already said.
SEE: Take a look at our primer on OpenAI’s talkative ChatGPT.
Google wants its search engine to be able to interpret and write code. Other ideas discovered in documents accessed by The New York Times include Google letting users make AI-generated pictures in image search, providing language-learning lessons through an AI chatbot and answering questions at the same time as navigating Google Chrome. The search in the latter would take into account both the internet-wide search and the page the user is actively using.
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ChatGPT reached 100 million monthly users in January, according to a UBS report, making it the fastest-growing consumer app in history. The business world is interested in ChatGPT too, trying to find uses for the writing AI throughout many different industries. This cheat sheet includes answers to the most common questions about ChatGPT and its competitors.
Jump to:
What is ChatGPT?
Who made ChatGPT?
How much does ChatGPT cost?
How to use ChatGPT
Criticisms of generative AI like ChatGPT
What are ChatGPT’s competitors?
The future of AI in business
What’s next for OpenAI?
What is ChatGPT?
ChatGPT is a free-to-use AI chatbot product developed by OpenAI. ChatGPT is built on the structure of GPT-4. GPT stands for generative pre-trained transformer; this indicates it is a large language model that checks for the probability of what words might come next in sequence. A large language model is a deep learning algorithm — a type of transformer model in which a neural network learns context about any language pattern. That might be a spoken language or a computer programming language.
The model doesn’t “know” what it’s saying, but it does know what symbols (words) are likely to come after one another based on the data set it was trained on. The current generation of artificial intelligence chatbots, such as ChatGPT, its Google rival Bard and others, don’t really make intelligently informed decisions; instead, they’re the internet’s parrots, repeating words that are likely to be found next to one another in the course of natural speech. The underlying math is all about probability. The companies that make and use them pitch them as productivity genies, creating text in a matter of seconds that would take a person hours or days to produce.
In ChatGPT’s case, that data set is a large portion of the internet. From there, humans give feedback on the AI’s output to confirm whether the words it uses sound natural.
SEE: OpenAI’s probability assessments were trained on Microsoft’s Azure AI supercomputer.
Several organizations have built this ability to answer questions into some of their software features too. Microsoft, which provides funding for OpenAI, rolled out ChatGPT in Bing search as a preview. Salesforce has added ChatGPT to some of its CRM platforms in the form of the Einstein digital assistant.
Who made ChatGPT?
ChatGPT was built by OpenAI, a research laboratory with both nonprofit and for-profit branches. At the time of its founding in 2015, OpenAI received funding from Amazon Web Services, InfoSys and YC Research and investors including Elon Musk and Peter Thiel. Musk has since cut ties with the company, while Microsoft currently provides $10 billion in funding for OpenAI.
How much does ChatGPT cost?
The base version of ChatGPT can strike up a conversation with you for free. For $20 per month, ChatGPT Plus gives subscribers priority access in individual instances, faster response times and the chance to use new features and improvements first. For example, right now ChatGPT Plus subscribers will be running GPT-4, while anyone on the free tier will talk to GPT-3.5.
For developers and organizations who don’t already have a specific contract with OpenAI, there is a waitlist for access to the ChatGPT API.
How to use ChatGPT
It’s easy to use the free version of ChatGPT. You need to sign up for an account with OpenAI, which involves fetching a confirmation code from your email; from there, click through and provide your name and phone number. OpenAI will warn you that the free version of ChatGPT is “a free research preview.” For the Plus version, you’ll see an “upgrade to Plus” button on the left side of the home page.
For businesses, ChatGPT can also write and debug code, as well as create reports, presentations, emails and websites. In general, ChatGPT can draft the kind of prose you’d likely use for work (“Write an email accepting an invitation to speak at a cybersecurity conference.”). ChatGPT can answer questions (“What are similar books to [xyz]?”) as well. Microsoft showed off these features in its announcement that OpenAI is coming to Word and some other parts of the 365 business suite.
OpenAI’s bug bounty program
OpenAI started a bug bounty program on April 12, offering between $200 and $20,000 to ethical hackers who find vulnerabilities in the code. More critical vulnerabilities net larger bounties.
OpenAI isn’t looking for solutions to problems with ChatGPT’s content (e.g., the known “hallucinations”); instead, the organization wants hackers to report authentication issues, data exposure, payments issues, security issues with the plugin creation system and more. Details about the bug bounty program can be found on Bugcrowd.
Criticisms of generative AI like ChatGPT
With more and more organizations adopting generative AI, many questions arise. Will AI be able to fill jobs currently held by humans? What privacy and ethical concerns does it raise? These questions apply to both ChatGPT and its competitors, since any generative AI can perform similar tasks.
Will ChatGPT result in people losing jobs?
Whether ChatGPT will take jobs away from humans is impossible to predict. Goldman Sachs says in an April report that a quarter to a half of humans’ workloads could be automated with generative AI. The financial institution notes that doesn’t necessarily mean those jobs will disappear – instead, most will be “only partially exposed to automation” – and it may lead to up to a 7% increase in global GDP.
Roles that are repetitive or based on very specific rules are most likely to be able to be performed by AI, Steven Miller, professor emeritus of information systems at Singapore Management University, told CNBC.
ChatGPT could lead to new job roles being created, too. At the very least, people will be needed to prompt, train and audit AI like ChatGPT. Most likely, we’ll see the kind of shuffle that comes with any major technological shift as some jobs change and others do not.
Some experts refer to the current wave of AI as similar to the early days of the internet. Technological limitations still exist, and some estimations about how many jobs would be lost through automation have proven exaggerated in the past. The IEEE points out that the AI industry will need to be aware of hardware limitations and costs. Companies may not find it practical to spend enough money on AI services in order to replace a large percentage of their workforce. Paying users of ChatGPT can make a maximum of 25 GPT-4 queries every three hours, IEEE points out.
In some jobs, the AI may remove the need for a first draft, MIT labor economics professor David Autor said in an interview with CBS MoneyWatch. A human will need to tweak the output and give in a unique angle or more varied wording, but ChatGPT could write the bare bones version of a speech or a blog post.
Ethical and privacy concerns about ChatGPT
Perhaps inspired by science fiction about AI taking over the earth, some high-profile players in tech urge caution about giving AI too much free rein. On March 22, 2023, a petition and open letter signed by Elon Musk and many others urged companies to pause large AI development until more safeguards can be built in.
OpenAI cautions that its products are not to be used for decisions in law enforcement or global politics. Privacy, which is perhaps a more pressing concern than global domination, led Italy to ban ChatGPT. OpenAI has since stated it wants to find a way to let ChatGPT work within the European Union’s strict privacy rules.
ChatGPT opens up questions about the ethics of using written content created by the algorithm. Posts created by AI should be clearly marked as such, but what about more casual communication such as emails? Business leaders should establish guidelines for when to be transparent about the use of ChatGPT or other AI at work.
What are ChatGPT’s competitors?
ChatGPT’s primary competitors are or could be Google’s Bard, Baidu’s Ernie, DeepMind’s Sparrow and Meta’s BlenderBot.
Google’s Bard
ChatGPT’s main competitor is Bard, Google’s AI generative AI chatbot. People who would like to try Bard’s chat function need to join a waitlist.
Now Google plans to add Bard into search. In comparison to ChatGPT, Bard focuses more on creating prose that sounds like a human could have spoken it naturally and less on being able to answer any question. Bard is built on Google’s Language Model for Dialogue Applications.
While Microsoft is ahead of the pack right now in terms of providing chat functions to productivity software, the company lags behind in terms of its search engine Bing. Google decision-makers allegedly pivoted to urgently roll out a competitor for Microsoft’s decision to add generative AI to Bing search. (Meanwhile, ChatGPT helped Bing reach 100 million daily users.
Baidu’s Ernie
The Chinese search engine Baidu plans to add a chatbot called Ernie. Baidu announced the upcoming change on March 16, at which point the initial showing disappointed investors.
DeepMind’s Sparrow
OpenAI competes with DeepMind, an artificial intelligence research laboratory owned by Alphabet. The two organizations are significantly different in terms of their aims. DeepMind focuses more on research and has not yet come out with a public-facing chatbot. DeepMind does have Sparrow, a chatbot designed specifically to help AI communicate in a way that is “helpful, correct and harmless.” DeepMind founder Demis Hassabis told The Independent in January 2023 that DeepMind may release a private beta version of Sparrow later in 2023.
Meta’s BlenderBot
Meta released BlenderBot in August 2022. The prototype BlenderBot from the company behind Facebook focuses on being able to chat, providing short, conversational replies rather than full paragraphs.
What about Apple?
According to The New York Times, Apple is working on leveraging the tech it has, especially Siri, to create a ChatGPT rival. More information about what the final product might look like is thin on the ground for now.
The future of AI in business
Will ChatGPT be common in online products in the future or is it a technological innovation forever in search of a greater use case? Today its “intelligence” is clearly still in the beginning stages, with OpenAI including disclaimers about inappropriate content or incorrect “hallucinations.” ChatGPT may put the words in a coherent order, but it won’t necessarily keep the facts straight.
Meanwhile, AI announcements that go viral can be good or bad news for investors. Microsoft’s stock price rose after the announcement of GPT-4, while Google’s stock dropped when Bard performed badly in a demonstration.
What’s next for OpenAI?
For now, OpenAI says it isn’t training GPT-5, the likely successor to today’s model. In a talk at MIT reported on by The Verge, OpenAI CEO Sam Altman pushed back against the open letter – an earlier draft of which had stated that a 5th generation was on the way; primarily, he criticized the letter’s lack of technical specificity.
“We are doing other things on top of GPT-4 that I think have all sorts of safety issues that are important to address and were totally left out of the letter,” Altman said.
He said no one should expect to see a GPT-5 rollout “for some time.”
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