Meta plans to bring generative AI to metaverse games

CIOs and chief technology officers (CTOs) have a critical role in capturing that value, but it’s worth remembering we’ve seen this movie before. New technologies emerged—the internet, mobile, social media—that set off a melee of experiments and pilots, though significant business value often proved harder to come by. Many of the lessons learned from those developments still apply, especially when it comes to getting past the pilot stage to reach scale. For the CIO and CTO, the generative AI boom presents a unique opportunity to apply those lessons to guide the C-suite in turning the promise of generative AI into sustainable value for the business. CEO Mark Zuckerberg has said that one area of focus is on creating “AI personas that can help people in a variety of ways.” It’s likely that this would tie into plans to incorporate generative AI into the company’s chat technology. This would make it possible to talk to these characters via the company’s chat platforms – the largest of which are Whatsapp and Messenger – in order to interact with Meta’s various services.

In evolving the architecture, CIOs and CTOs will need to navigate a rapidly growing ecosystem of generative AI providers and tooling. Cloud providers provide extensive access to at-scale hardware and foundation models, as well as a proliferating set of services. CIOs and CTOs will need to assess how these various capabilities are assembled and integrated to deploy and operate generative AI models. Generative AI refers to a trending class of machine learning applications that are able to create new data, including text, images, video, or sounds, based on a large dataset on which it has been trained. Examples of generative AI applications include ChatGPT – the fastest-growing application of all time, as well as image creation tools such as Dall-E and Stable Diffusion. To protect data privacy, it will be critical to establish and enforce sensitive data tagging protocols, set up data access controls in different domains (such as HR compensation data), add extra protection when data is used externally, and include privacy safeguards.

But the benefits are unevenly distributed depending on roles and skill levels, requiring leaders to rethink how to build the actual skills people need. Realistically, the platform team will need to work initially on a narrow set of priority use cases, gradually expanding the scope of their work as they build reusable capabilities and learn what works best. Technology leaders should work closely with business leads to evaluate which business cases to fund and support. Instead, CIOs and CTOs should work with risk leaders to balance the real need for risk mitigation with the importance of building generative AI skills in the business. This requires establishing the company’s posture regarding generative AI by building consensus around the levels of risk with which the business is comfortable and how generative AI fits into the business’s overall strategy.

For example, a retailer may upload a photo of a red dress, and Meta’s AI can create variations of red dresses with different background colors and text overlays that are designed for multiple platforms like in-feed and Reels. Meta also said it plans to roll out text prompts that allow advertisers to type in what they want their ad to look like. The focus will be Horizon, Meta’s family of metaverse games, apps and creation resources. But it might expand to games and experiences on “non-Meta” platforms like smartphones and PCs. While other companies like Google and OpenAI might have gained more public attention in specific AI areas, Meta is still a prominent player in AI research and development.

This can only be possible if your GenAI model is trained on your company’s data that is relevant to your needs. This allows generative AI to customize itself and better fit the requirements of your business. The easiest way to identify a function within your chosen domain that could be made more productive through GenAI is by focusing on job roles that are challenging to retain and hire for. These roles often involve repetitive tasks and offer limited career advancement opportunities. Automating these tasks can liberate employees to concentrate on more strategic aspects of their work.

OpenAI: Everything You Need to Know About the Company That Started a Generative AI Revolution

Kanerika’s team can help you identify your objectives and build the right generative AI solution for your requirements. By implementing a Language Model-based ticket response system, Kanerika’s team of GenAI specialists helped them achieve a 70% increase in customer satisfaction, reduced staffing costs, and quicker ticket resolution times. The next step in our Generative AI CTO Guide is about crafting a seamless user experience (UX) and interface (UI) for your GenAI model.

Kanerika recently worked with a B2B SaaS company facing challenges in operational efficiency and customer support. They are the architects who can prevent a “death of the use case” scenario, a common pitfall in many organizations. By collaborating with CEOs and CFOs, they can identify the most lucrative opportunities that GenAI can unlock. A SnapLogic study found that 93% of organizations prioritize AI and ML, but over half lack the in-house skills and individuals for execution. AI will rule the future, but how do we create that future for our organizations? Let’s face it — day-to-day business operations are not exactly exciting for employees.

Meta To Debut Ad-Creating Generative AI this Year, CTO Says (nikkei.com)

Similar to the difference between writing and editing, code review requires a different skill set. Furthermore, software developers will need to learn to think differently when it comes to coding, by better understanding user intent so they can create prompts and define contextual data that help generative AI tools provide better answers. It’s released, in its „GPT“ family, large language models, or LLMs, which are AI systems trained on huge data sets to understand and generate human language. Those are deep-learning models that process additional content types, like video, audio and images. Meta’s Facebook AI division has developed its own image generation technology that it has named Instance-Conditioned Generative Adversarial Networks (IC-GAN). According to its researchers, unlike standard GAN-based image generators, it can be used to create images that are more diverse than the images contained within their training datasets.

GPT-4o has the same context window, while a prior model, GPT-3.5 Turbo, has a context window of 16,000 tokens. He found that ChatGPT 4 is smarter and generates more-thoughtful answers that can synthesize complex information. „ChatGPT 4 really impresses when you need more-specialized answers to specific questions (like college-level philosophy questions),“ Khan wrote.

There are millions of GPTs available, including ones for fitness, haikus and books. Further, OpenAI says it filters out data it doesn’t want its models to learn, like hate speech, adult content and spam. The information fed into the LLM is called training data, and OpenAI, like other AI makers, hasn’t shared exactly what information is in its training data. Fine-tuning is the process of adapting a pretrained foundation model to perform better in a specific task. This entails a relatively short period of training on a labeled data set, which is much smaller than the data set the model was initially trained on. This additional training allows the model to learn and adapt to the nuances, terminology, and specific patterns found in the smaller data set.

OpenAI is the AI power player founded in 2015 that launched a new era of AI accessibility and creativity. In less than two years, the generative AI chatbot ChatGPT has become a household name alongside products like the iPhone, Windows and Google Search. Its ChatGPT chatbot quickly set the tone for what we can expect from Big Tech in the coming years. Meta CEO Mark Zuckerberg reassured his employees about the company’s strategy and efforts regarding artificial intelligence. This comes after the company conducted its latest round of job cuts two weeks ago.

Clearly, just entering prompts is not the challenge that businesses seem to face today. It is problem formulation — the ability to identify, analyze, and delineate problems. This is where your team will play the most crucial role in identifying the right problems and getting the appropriate answers from your generative AI model. For instance, a marketing manager might require a suite of tools ranging from Google Docs for content creation to Salesforce for customer relationship management.

Adobe’s survey shows that 62% of UX designers already use AI to automate tasks. Work closely with your trio team to design the prompts that will steer the GenAI model’s responses. Leverage your team’s expertise in understanding business requirements, engineering the right prompts, and overseeing the technical execution of your AI model. Step five of our Generative AI CTO Guide is all about defining your intentions, objectives, and desired output with your GenAI model. It’s crucial to have a skilled human in the loop, especially during the initial stages, to provide oversight and ensure that the AI aligns with your business goals. By meticulously selecting the appropriate data sources and understanding the expansive capabilities of GenAI, you’re setting the stage for making your chosen persona exceptionally productive.

• Organizations will use many generative AI models of varying size, complexity, and capability.
• Large language models (LLMs) make up a class of foundation models that can process massive amounts of unstructured text and learn the relationships between words or portions of words, known as tokens.
• However, despite a switch of focus in recent months on AI, Meta and Zuckerberg are still, to some extent sticking to their guns.
• A study conducted within a Fortune 500 company revealed that implementing GenAI in customer support not only boosted productivity but also significantly improved customer satisfaction.

The precise meaning of this term has been much-debated, but it usually refers to a “next generation” iteration of the internet featuring more immersive environments possibly rendered in virtual reality (VR), avatars, and a shared online experience. The company has been investing in AI research since 2013 and has made significant progress. Meta’s research output is second only to Google in the number of published AI studies, according to a 2022 analysis by AI research analysis platform Zeta Alpha. Mintlify offers a collection of documentation-authoring tools, including tools that can auto-generate docs from codebases. “[I] expect we’ll start seeing some of them [commercialization of the tech] this year.

While Meta’s metaverse efforts haven’t panned out as expected, it still seems to be pushing on the idea of creating virtual worlds through generative AI. Bosworth told Nikkei that large language models (LLMs) — like OpenAI’s GPT-4 and Google’s PaLM — will help with 3D model creation as you’ll just have to describe them. Bosworth insists that Meta remains on the cutting edge of the technology, which has already been commercialized by ChatGPT creator OpenAI. Meta’s large research organization has been investing in artificial intelligence for over a decade, and Bosworth expects to see the commercialization of the tech this year with the help of their new team, the generative AI team. Though the initial novelty of AI-generated content may have worn off a bit, tech companies continue to push boundaries with increasingly powerful models, new ways to interact with chatbots, and additional functionality such as search. As of January, SEO strategy site Backlinko found that ChatGPT had nearly 70% market share among subscription-based AI tools.

In some instances, such as creating a customer-facing chatbot, strong product management and user experience (UX) resources will be required. Because nearly every existing role will be affected by generative AI, a crucial focus should be on upskilling people based on a clear view of what skills are needed by role, proficiency level, and business goals. Training for novices needs to emphasize accelerating their path to become top code reviewers in addition to code generators.

This Github repository is dedicated to the ongoing development of Stability AI’s StableLM series of language models, including the recently released Stab… Because the entire process is extremely easy, it resembles a typical drive-thru experience. Simultaneously, it replaces human staff with automated bots that are trained to have conversations with customers. This frees up the human staff to work around the kitchen and focus on the preparation of food and delivery.

Generative AI technology, which can instantly create sentences and graphics, has been commercialized by ChatGPT creator OpenAI. However, Meta’s CTO Andrew Bosworth insists that Meta remains at the cutting edge, with its recently formed generative AI team. For example, Meta shared that the skincare brand Fresh saw a five-time incremental return on ads spend by running Advantage+ shopping campaigns with Shops ads and generative AI text variations. Similarly, Casetify saw a 13% increase in return on ad spend when testing the background generation feature. Meta will continue to offer these tools at no additional cost to the user, in the hopes that increased ad performance encourages companies to continue to advertise with Meta.

Once this chatbot is built, it can be used endlessly, 24×7, to cater to all patient needs. It can be further customized later to add more functionalities that are relevant to the business. This paper-based, time-consuming process can take hours or even days to approve simple procedures like MRIs or specialist visits. According to a survey by the American Medical Association, 92% of clinicians believe that these lengthy protocols negatively affect timely patient care and clinical outcomes.

Generative AI is poised to be one of the fastest-growing technology categories we’ve ever seen. Tech leaders cannot afford unnecessary delays in defining and shaping a generative AI strategy. While the space will continue to evolve rapidly, these nine actions can help CIOs and CTOs responsibly and effectively harness the power of generative AI at scale.

For the past couple of years, Meta has leaned heavily into its AI ad product, Advantage+, which helps advertisers find the best platform and ad to place in front of someone. The tool is designed to steer advertisers toward finding audiences that lead to strong ad performance, which is measured in metrics like sales or website traffic. Meta plans to bring more generative AI tech into games, specifically VR, AR and mixed reality games, as the company looks to reinvigorate its flagging metaverse strategy.

Just visualize their recent ad campaign — dubbed “Masterpiece” — where AI breathes life into iconic artworks, making them dance off the canvas. It played the role of a psychotherapist and gave human-like responses to users. Therefore, convincing a majority of the population that it was more than just a computer. Musk filed a lawsuit against OpenAI, accusing the startup of abandoning its nonprofit mission, but he later dropped it, and then he refiled it, earlier this month, alleging fraud and breach of contract. In response, OpenAI referred to its blog post about Musk’s initial lawsuit. Sutskever, who was the chief scientist at OpenAI until June, disagreed with Altman over how rapidly AI should develop amid concerns it could eventually harm humanity without the right constraints.

Hegeman said Meta is „working through some of the specifics“ about how that policy applies to ads created with gen AI. „What we are hearing from advertisers is that these generative AI tools are saving time and resources while increasing productivity,“ he said. Now, advertisers can begin using Advantage+ to create the visuals and text of those ads. Meta’s AI can create full image variations — though advertisers need to feed an image to Meta to create an ad.

The same month he left OpenAI, Sutskever founded an AI company called Safe Superintelligence Inc., or SSI. You can foun additiona information about ai customer service and artificial intelligence and NLP. According to the website, its singular goal is safe superintelligence, or AGI. In his review, CNET’s Stephen Shankland called Dall-E 3 „a marvel“ among image generators that does well with both realistic and surreal images and encourages you to get creative.

Meta says that companies are already seeing improved ad performance from leveraging some of these tools. All of the generative AI features are available in Meta’s Ads Manager through Advantage+ creative, Meta’s hub for optimizing user ad content. The image expansion feature is being upgraded to include Reels and Feed on both Instagram and Facebook, making it easier for users to adjust the same content across aspect ratios and eliminating the need for manual adjustments. TOKYO — Facebook owner Meta intends to commercialize its proprietary generative artificial intelligence by December, joining Google in finding practical applications for the tech.

According to the CTO Andrew Bosworth, the shipment of the tools will happen later this year. Alvin Bowles, VP of Meta’s global business group, said that Meta is working with agencies and brands to educate them on how to use generative AI tools to make their jobs more efficient. However, despite a switch of focus in recent months on AI, Meta and Zuckerberg are still, to some extent sticking to their guns.

The advantages of this are that it requires less compute power and resources to retrain in order to test new approaches and use cases. Models such as this could conceivably run on far smaller devices than the cloud servers that are needed for ChatGPT or Bard – potentially opening the way for self-contained instances to run on personal computers or even smartphones. This could have important implications for businesses that want to use generative language models while keeping their data private.

Or, make the entire experience of communicating with the bot so seamless that it resembles a human interaction. The business team and technology team are on the same page and agree to a balanced approach that sees them scale their company’s GenAI capabilities while balancing costs and potential changes that may arise from it. McKinsey’s research highlights that generative AI can boost productivity in marketing by around 10% https://chat.openai.com/ and in customer support by up to 40%. Therefore, CIOs and CTOs need to work closely with their business counterparts and exchange information to identify the perfect balance between return on investment (ROI) and technological feasibility. OpenAI also offers APIs for developers who want to build new applications based on OpenAI technology or custom AI apps called GPTs, which you can create and share in OpenAI’s app store.

Each archetype has its own costs that tech leaders will need to consider (Exhibit 1). While new developments, such as efficient model training approaches and lower graphics processing unit (GPU) compute costs over time, are driving costs down, the inherent complexity of the Maker archetype means that few organizations will adopt it in the short term. Instead, most will turn to some combination of Taker, to quickly access a commodity service, and Shaper, to build a proprietary capability on top of foundation models.

Omneky, which presented at TechCrunch Disrupt last year, was using OpenAI’s DALLE-2 and GPT-3 to create campaigns. Movio, which is backed by IDG, Sequoia Capital China and Baidu Ventures, is using generative AI to create marketing videos. It can generate highly realistic, multilingual speech as well as other types of audio, i… This is your roadmap for everything from infrastructure and continuous performance upgrades to human-in-the-loop oversight and security measures. As well as measuring impact, and avenues for continuous improvement to ensure you’re on the right path. Generative AI can streamline these processes and reduce friction by automating the entire process through a digitalized chatbot that gathers information and verifies all details.

Generative AI is a type of AI that can create new content (text, code, images, video) using patterns it has learned by training on extensive (public) data with machine learning (ML) techniques. “So previously, if I wanted to create a 3D world, I needed to learn a lot of computer graphics and programming. In the future, you might be able to just describe the world you want to create and have the large language model generate that world for you. And so it makes things like content creation much more accessible to more people,” he said.

Additionally, users can overlay text on those images, selecting from dozens of font typefaces to complete the ad, as seen below. Now, the company is adding new image and text generation capabilities, the highlight being a new image variation feature that can create alternate iterations of your content based on the original creative. On Tuesday, Meta unveiled new generative AI features and upgrades that build on its current offerings to assist businesses in creating and editing new ad content, aiming to make the process quicker and more efficient. In an interview with Nikkei Asia, Meta’s CTO Andrew Bosworth, said the company expects to ship tools to create ads with AI that help a company make different images for different audiences.

Our latest empirical research using the generative AI tool GitHub Copilot, for example, helped software engineers write code 35 to 45 percent faster.5“Unleashing developer productivity with generative AI,” June 27, 2023. Highly skilled developers saw gains of up to 50 to 80 percent, while junior developers experienced a 7 to 10 percent decline in speed. That’s because the output of the generative AI tools requires engineers to critique, validate, and improve the code, which inexperienced software engineers struggle to do. Recent advances in integration and orchestration frameworks, such as LangChain and LlamaIndex, have significantly reduced the effort required to connect different generative AI models with other applications and data sources.

Meta plans to monetize its proprietary generative AI technology by December, joining Google in exploring practical applications. The company has been investing in AI for over a decade and recently created a new generative AI team to focus on commercialization. Generative AI is great at churning out quality creative content at impressive speed and scale, so we’ll continue to see more of these applications that support marketers in the coming months. Recently, Adobe announced a suite of generative AI tools marketers can use to help with everything from generating content for a campaign to deploying it. In the upcoming months, it will be upgraded to include user text prompts that can customize what the model generates to better fit a user’s specific vision.

OpenAI says its LLMs use information that’s publicly available on the internet; info the company licenses from third parties; and data from OpenAI’s users and human trainers. However, the models have cut-off dates, which means their training data is current only up to a certain date. OpenAI is the company behind the chatbot, which hit the market in November 2022, spurring a wave of AI-powered creativity that quickly mesmerized us, in text, images and videos. Other companies — tech titans and fellow startups — saw the effusive public reaction and jumped on the bandwagon with their own tools. Practically speaking, that will mean building the skills of junior employees as quickly as possible while reducing roles dedicated to low-complexity manual tasks (such as writing unit tests). It’s likely that they are hoping that this democratizing effect will be the catalyst for more of its billion-plus customer base to make the leap from the two-dimensional pages of Facebook to the three-dimensional worlds of Horizons.

The Text-to-Video Synthesis Colab is a Github repository that includes various models for generating videos from text. The success of your GenAI project hinges on robust KPIs that cover a spectrum of these metrics. These KPIs serve as the pulse of your project, offering insights into your AI model’s business impact. This case illustrates how a well-executed LM operations plan can not only solve immediate challenges but also pave the way for a company’s sustainable growth. The best example of this would be the recent partnership between fast food chain, Wendy’s and Google.

Meta’s AI research began in 2013 and is currently second only to Google in the number of published studies. The tool will allow advertisers to create unique and highly targeted ads, which could potentially increase engagement and save time and money. However, considering how Meta was used in the past by bad actors to manipulate users Chat GPT in a very perversive way, it is easy to imagine how this new technology can become a problem. The company’s CTO claims there’s no need for concern, but we should always be cautious and consider the incentives at play. It’s possible (just possible) that Meta may prioritize profits over mitigating potential negative impacts.

Whether it’s analyzing the impact of ad spend on customer perceptions or tracking a competitor’s R&D investments, the quest for actionable insights is a never-ending task. And it’s not just a one-off endeavor; it’s an ongoing cycle that involves convening experts, conducting research, and compiling information. It’s a process that everyone, from executives to new hires, finds frustratingly time-consuming. OpenAI was founded by a group of research engineers and scientists, as well as CEO Altman, entrepreneur Elon Musk, machine learning expert Ilya Sutskever and president and chairman Greg Brockman.

He considers the petition’s request not only unrealistic but also ineffective. Meta’s new features could also make it easier for businesses to reach their target audiences, as a shoot can be tweaked to suit many different interests without having to go through extensive project planning to bring a new idea to life. The company, which began full-scale AI research in 2013, stands out along with Google in the number of studies published. With a fresh $35M in the bank, French cleantech startup Calyxia has profitability within sight. During the call, Meta also highlighted that despite the $1 billion annual revenue rate, Reels are not generating enough money. DeepFloyd IF is a modular, state-of-the-art open-source text-to-image model composed of a frozen text encoder and three cascaded pixel diffusion modules….

It could also allow businesses to implement these services into their own Facebook pages and Whatsapp channels, effectively allowing any business to offer its own automated, AI-powered customer service and feedback agents. Meta aims to use AI to improve ad effectiveness and apply the technology across all its products, including Facebook and Instagram. The company also plans to incorporate the technology into the development of the metaverse, making content creation more accessible.

But that’s not all; nearly half of the organizations experienced accelerated innovation, and 48% saw a boost in employee productivity. Mastercard is setting a new standard in customer service by integrating ChatGPT into their existing chatbot platform. It’s a virtual assistant that can handle a broad spectrum of customer needs. Thereafter, offering personalized recommendations that make it easier for users to analyze and make financial decisions.

The same technology is also usable when using Instagram filters for Stories. The social media giant Meta is planning to invest in generative AI at the end of 2023. With this action, the company is commercializing the use of the technology to improve its ad creation in its apps. One of the problems advertisers have experienced with Advantage+ is a lack of control over where their ads appear and capping their ad spend — similar to Google’s AI ad product called Performance Max. In April, Meta announced that it would begin labeling gen AI content on its platform this month.

The new efforts come as a blockbuster product remains elusive for Meta’s Reality Labs, the division responsible for the company’s sundry metaverse projects, including its Meta Quest headset. While Meta has sold tens of millions of Quest units, it’s struggled to attract users to its Horizon mixed reality platform — and claw back from billions of dollars in operating losses. Additionally, as Meta focuses on developing the metaverse, advertisers must adapt their strategies to effectively engage users in this new virtual space. Embracing AI technology will be crucial for creating immersive and interactive advertising experiences in the metaverse. According to Google’s research, 66% of organizations using GenAI reported increased operational efficiency, and an impressive 57% noted an improved customer experience.

66% of organizations using GenAI reported increased operational efficiency while an impressive 57% noted an improved customer experience. Read our Generative AI CTO Guide to help your organization get started on your generative journey. When OpenAI was thinking about switching to a for-profit model in 2017, Musk, according to an OpenAI blog post, wanted the startup to merge with his electric-car company, Tesla, or to give him majority equity, board control and the CEO title. Asked by CNN for a response to the blog post at the time, lawyers for Musk declined to comment.

At its annual developers conference in June, Apple announced a partnership with OpenAI. The iPhone maker plans to integrate ChatGPT into its iOS smartphone operating system; its tablet operating system, iPadOS; and its computer operating system, MacOS. It also plans to offer ChatGPT as an option to users querying its Siri voice assistant. These models were meta to adcreating generative ai cto long available to developers, but it was the release of GPT-3.5 and the ChatGPT interface in 2022 that made it possible for virtually anyone to use generative AI, sparking the transformative era we’re in now. Prompts can include text or verbal requestsin plain English for nearly anything, as long as the query falls within OpenAI’s safety standards.