ai-collection ai-collection: The Generative AI Landscape A Collection of Awesome Generative AI Applications
Machines can analyze a set of data and find patterns in it for a multitude of use cases, whether it’s fraud or spam detection, forecasting the ETA of your delivery or predicting which TikTok video to show you next. It became a wholly owned subsidiary of Alphabet Inc., in 2015 after its acquisition by Google in 2014. DeepMind has created a neural network or a Neural Turing machine that tries to replicate the short-term memory of the human brain. By subscribing to email updates you can expect thoroughly researched perspectives and market commentary on the trends shaping global markets.
In addition, content may not be truly original, which may require revision for context. Her current research agenda focuses on digital technologies for Operational Excellence including digital twins and software solutions for industrial risk and asset management. Malavika previously worked at Frost & Sullivan, managing and delivering advisory projects for clients involving expansion, acquisition, benchmarking and product development strategies.
Many public tech companies spend hundreds of millions per year on model training, either with external cloud providers or directly with hardware manufacturers. What we now call generative AI wouldn’t exist without the brilliant research and engineering work done at places like Google, OpenAI, and Stability. Through novel model architectures and heroic efforts to scale training pipelines, we all benefit from the mind-blowing capabilities of current large language Yakov Livshits models (LLMs) and image-generation models. In the legal and government sectors, generative AI aids in legal document analysis, contract generation, and natural language processing. AI-powered chatbots handle initial client interactions, assisting with legal inquiries and providing relevant legal information. Additionally, generative models assist in analyzing large volumes of legal texts and documents, streamlining legal research and decision-making processes.
Generative AI in extensions leads to a personalized web browsing experience, assisting users in navigating the vast amount of online information more effectively. One of Replicate’s key features is private sharing, which allows users to share their models with a selected group of users. This attribute can be crucial for collaboration or for safeguarding sensitive data. It also provides version control for machine learning models, enabling users to track changes over time. This could be particularly beneficial for debugging or tracking the performance improvements of your models. Furthermore, Replicate enables monitoring metrics such as accuracy and latency, which are crucial for evaluating model performance.
She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers. When people can easily switch to another company and bring their financial history with them, that presents real competition to legacy services and forces everyone to improve, with positive results for consumers. For example, we see the impact this is having on large players being forced to drop overdraft fees or to compete to deliver products consumers want. When we look across the Intuit QuickBooks platform and the overall fintech ecosystem, we see a variety of innovations fueled by AI and data science that are helping small businesses succeed. This presents a tremendous opportunity that innovation in fintech can solve by speeding up money movement, increasing access to capital, and making it easier to manage business operations in a central place.
High-level tech stack: Infrastructure, models, and apps
By inputting their existing work, they can generate variations, providing them with new creative directions that they may not have considered before. Improvements in generative AI technology could help firms find ways to harness imperfect data, while mitigating privacy concerns and regulations. Generative AI is revolutionizing the way we live, work, and interact with the world around us. By creating content, designs, and solutions never before imagined, these intelligent systems are breaking barriers and opening up new possibilities in countless industries. From art and music to business and science, generative AI is reshaping our understanding of creativity and innovation, propelling us into a bold new age of discovery and progress.
Rather, before taking the judge position Faruqui was one of a group of prosecutors in the U.S. Attorney’s office in Washington, D.C., that called themselves the “Bitcoin Strikeforce,” and worked with agencies like the IRS and FBI in federal investigations. There, Faruqui prosecuted cases that involved terrorism, child pornography, and weapons proliferation. Particularly well known was a case involving a dark-web site called “Welcome to Video,” which had facilitated some 360,000 downloads of sexually exploitative videos of children to 1.28 million members worldwide using bitcoin. Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle.
Wizeline’s Map of the Generative AI Landscape
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.
Then the other big category where there has been a lot has been in the text space. So there’s a lot of these marketing Gen AI companies, and some of them are really working. We’re seeing it evolve, as well, where people started from shorter-form generations and now we’re getting really, really long form. For creative content generation, unsupervised learning might be suitable, allowing the AI to generate content freely. Supervised learning with labeled data may be more effective for specific tasks like lead scoring. Generative AI models rely on large datasets for training, and it is essential to ensure your agency can access quality data relevant to your B2B niche.
Efforts to make LLMs more accessible and energy-efficient are ongoing but untested. Introduction to Generative AI speaks to a diverse audience intrigued by the complexities of AI and its generative models. Nearly everything in generative AI passes through a cloud-hosted GPU (or TPU) at some point. Whether for model providers / research labs running training workloads, hosting companies running inference/fine-tuning, or application companies doing some combination of both — FLOPS are the lifeblood of generative AI. For the first time in a very long time, progress on the most disruptive computing technology is massively compute bound. Perhaps the clearest takeaway for model providers, so far, is that commercialization is likely tied to hosting.
Cohere is a language AI platform that offers a user-friendly API and platform to power multiple use cases for global companies. Their large language models enable powerful capabilities such as content generation, summarization, and search at a massive scale. Their Yakov Livshits high-performance, secure, and customizable language models work on public, private, or hybrid clouds to ensure data security and exceptional support. Cohere’s generative AI tools allow users to write product descriptions, blog posts, articles, and marketing copy.
- Epic’s recent partnership with Microsoft and initiatives around patient-messaging demonstrate their rapid expansion into the gen AI health system landscape, which will make it difficult for startups to enter the space.
- You can compose landscape design entirely using provided design elements or switch to AI Landscape Design Stylist and ask it to generate more designs based on your work.
- Healthcare is an industry that still relies today on fax machines as a primary means of communication and previous technology “transformations” have paradoxically increased provider burdens and diminished their efficiency.
- In the near term, generative AI models will move beyond responding to natural language queries and begin suggesting things you didn’t ask for.
- This functionality allows large quantities of data to be read or written at a rate much faster than that achievable with a single path.
Generative AI (see Part IV) has been the one very obvious exception to the general market doom-and-gloom, a bright light not just in the data/AI world, but in the entire tech landscape. For a while in 2022, we were in a moment of suspended reality – public markets were tanking, but underlying company performance was holding strong, with many continuing to grow fast and beating their plans. In prior years, we tended to give disproportionate representation to growth-stage companies based on funding stage (typically Series B-C or later) and ARR (when available) in addition to all the large incumbents.
Developed by NVIDIA’s Applied Deep Learning Research team in 2021, the Megatron-Turing model consists of 530 billion parameters and 270 billion training tokens. Nvidia has provided Yakov Livshits access via an Early Access program for its managed API service to its MT-NLG model. Google AI, formerly known as Google Research, is the AI research and development arm of Google.
And then, you know, obviously, they’ll have different views, and we make a decision based on what people say in front of us. Lawyers are trying to take different frameworks from one topic and apply them to another, and then convince you that that is or is not appropriate. Being a judge is very different because you’re evaluating what the parties present to you as the applicable legal frameworks, and deciding how new, groundbreaking technology fits into legal frameworks that were written 10 or 15 years ago.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers. Matt Turck is a VC at FirstMark, where he focuses on SaaS, cloud, data, ML/AI, and infrastructure investments. However, founders built great startups that could not have existed without the mobile platform shift – Uber being the most obvious example. We’ve long argued in prior posts that the success of data and AI technologies is that they eventually will become ubiquitous and disappear in the background. However, Microsoft was forced by competition (or could not resist the temptation) to open Pandora’s box and add GPT to its Bing search engine.