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{"id":13517,"date":"2025-03-26T20:27:02","date_gmt":"2025-03-26T13:27:02","guid":{"rendered":"https:\/\/blog.momasa.id\/?p=13517"},"modified":"2025-03-30T14:31:14","modified_gmt":"2025-03-30T07:31:14","slug":"meta-to-debut-ad-creating-generative-ai-this-year","status":"publish","type":"post","link":"https:\/\/blog.momasa.id\/meta-to-debut-ad-creating-generative-ai-this-year\/","title":{"rendered":"Meta to debut ad-creating generative AI this year, CTO says"},"content":{"rendered":"

Meta plans to bring generative AI to metaverse games<\/h1>\n<\/p>\n

\"meta<\/p>\n

CIOs and chief technology officers (CTOs) have a critical role in capturing that value, but it\u2019s worth remembering we\u2019ve seen this movie before. New technologies emerged\u2014the internet, mobile, social media\u2014that 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 \u201cAI personas that can help people in a variety of ways.\u201d It\u2019s likely that this would tie into plans to incorporate generative AI into the company\u2019s chat technology. This would make it possible to talk to these characters via the company\u2019s chat platforms \u2013 the largest of which are Whatsapp and Messenger \u2013 in order to interact with Meta\u2019s various services.<\/p>\n<\/p>\n

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 \u2013 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.<\/p>\n<\/p>\n

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\u2019s 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\u2019s overall strategy.<\/p>\n<\/p>\n

\"meta<\/p>\n

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\u2019s family of metaverse games, apps and creation resources. But it might expand to games and experiences on \u201cnon-Meta\u201d 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.<\/p>\n<\/p>\n

This can only be possible if your GenAI model is trained on your company\u2019s 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.<\/p>\n<\/p>\n

OpenAI: Everything You Need to Know About the Company That Started a Generative AI Revolution<\/h2>\n<\/p>\n

Kanerika\u2019s 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\u2019s 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.<\/p>\n<\/p>\n

Kanerika recently worked with a B2B SaaS company facing challenges in operational efficiency and customer support. They are the architects who can prevent a \u201cdeath of the use case\u201d 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\u2019s face it \u2014 day-to-day business operations are not exactly exciting for employees.<\/p>\n<\/p>\n

Meta To Debut Ad-Creating Generative AI this Year, CTO Says (nikkei.com)<\/h2>\n<\/p>\n

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\u2019s 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.<\/p>\n<\/p>\n

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.<\/p>\n<\/p>\n

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.<\/p>\n<\/p>\n

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.<\/p>\n<\/p>\n

Clearly, just entering prompts is not the challenge that businesses seem to face today. It is problem formulation \u2014 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.<\/p>\n<\/p>\n

Adobe\u2019s 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\u2019s responses. Leverage your team\u2019s 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\u2019s 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\u2019re setting the stage for making your chosen persona exceptionally productive.<\/p>\n<\/p>\n