5 Amazing Ways Meta Facebook Is Using Generative AI

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.

The latest GPT model, GPT-4o, is a multimodal model, which means it understands images, audio and video as well. Early generative AI use cases should focus on areas where the cost of error is low, to allow the organization to work through inevitable setbacks and incorporate learnings. Beyond training up tech talent, the CIO and CTO can play an important role in building generative AI skills among nontech talent as well. Besides understanding how to use generative AI tools for such basic tasks as email generation and task management, people across the business will need to become comfortable using an array of capabilities to improve performance and outputs. The CIO and CTO can help adapt academy models to provide this training and corresponding certifications.

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.

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.

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.

French cleantech startup Calyxia nets $35M to tackle microplastics pollution

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.

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.

h2oGPT – The world’s best open source GPT

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.

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 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.

The same month he left OpenAI, Sutskever founded an AI company called Safe Superintelligence Inc., or SSI. 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.

Are EV ‚Charger Hogs‘ Ruining the EV Experience?

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.

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.

Answering these questions will provide you with a comprehensive understanding of where generative AI can be most effectively deployed in your organization. This makes them incredibly versatile, capable of performing a wide array of tasks like Q&A, summarization, and open-ended content generation without requiring additional data or tuning. Recognizing this need, our team got together to create this “Generative AI CTO Guide” for you and your organization to get started on your generative journey. Read ahead to explore the best practices and industry trends that can help you navigate your organization’s journey into the realm of GenAI. Yet, here we are in 2023 — a pivotal year in the growth and popularity of artificial intelligence (AI), with generative AI (GenAI) models available at every individual’s fingertips. The New York Times is among the publications that have sued OpenAI (and Microsoft) over unauthorized use of their content to train AI models.

• Facebook – Meta’s biggest platform and the world’s biggest social network – primarily makes money by allowing businesses to advertise on its pages.
• To mitigate risk to intellectual property, CIOs and CTOs should insist that providers of foundation models maintain transparency regarding the IP (data sources, licensing, and ownership rights) of the data sets used.
• But diving into GenAI without a clear strategy can lead to stalled projects and wasted investments.
• Cost calculations can be particularly complex because the unit economics must account for multiple model and vendor costs, model interactions (where a query might require input from multiple models, each with its own fee), ongoing usage fees, and human oversight costs.
• The advantages of this are that it requires less compute power and resources to retrain in order to test new approaches and use cases.

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 Chat GPT 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.

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.

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.

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.

With a deep understanding of the technical possibilities, the CIO and CTO should identify the most valuable opportunities and issues across the company that can benefit from generative AI—and those that can’t. 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. This enables LLMs to generate natural-language text, performing tasks such as summarization or knowledge extraction. LLaMA is deliberately designed as a smaller language model – its largest model is trained on 65 billion parameters as opposed to GPT-4’s reported one trillion parameters.

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.

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.

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.

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.

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.

You can foun additiona information about ai customer service and artificial intelligence and NLP. Google Meet on desktop Chrome now automatically enters picture-in-picture mode when you switch tabs, allowing users to keep track of calls easily.

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.

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 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.

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.

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.

Charting the Course: Creating a Business Roadmap for Generative AI

Meta recently pivoted its metaverse platform strategy, allowing third-party headset manufacturers to license some of the Quest’s software-based features, like hand and body tracking. At the same time, Meta has ramped up investments in metaverse game projects meta to adcreating generative ai cto — reportedly as a product of Meta CEO Mark Zuckerberg’s newfound personal interest in developing gaming for Quest headsets. While this tri-process seems pretty successful for organizations at the moment, we may not have to depend on it for too long.

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.

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.

With consumer engagement on those two initiatives so far proving underwhelming, more recently, it has focused efforts on the current hot topic of the technology world – generative AI. Generative AI has begun to trickle into game development, with companies like Disney-backed Inworld and Artificial Agency applying the tech to create more dynamic game dialogues and narratives. A number of platforms now offer tools to generate game art assets and character voices via AI — to the chagrin of some game creators who fear for their livelihoods. Social media feeds are an ideal place to advertise, and a well-executed campaign can help businesses grow significantly — but creating them is a lot of work. Meta’s new generative artificial intelligence (AI) tools aim to help make curating the perfect ad easier.

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.

OpenAI has also developed text-to-image models in the Dall-E family and has developed a text-to-video model called Sora that is expected to be released later this year. App Researcher and Reverse Engineer Alessandro Paluzzi revealed just a few days ago that Instagram might be working on an AI chatbot that can answer questions and give advice, depending on users‘ picked personalities out of 30. This will help users who find it challenging to write messages or simply type a comment.

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% 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.

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 https://chat.openai.com/ 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.

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.

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.

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.