??Generative AI & Industrial IoT??: A Match in Heaven? (UPDATED!)
??Fabio Bottacci
Senior Business Advisor / Venture Partner | Executive Director Business Development / Startups GTM Strategy & Execution | Industrial IoT + AI GenAI Expert & Evaluator @Horizon Europe Funding | HBR Advisory Council Member
OpenAI | ChatGPT
Prompt: {{{Generative AI IoT}}}
???Generative AI and IoT (Internet of Things) are two rapidly evolving fields that are having a significant impact on various industries. Generative AI involves using artificial intelligence algorithms to generate novel content, such as images, music, and text. On the other hand, IoT refers to a network of physical devices, vehicles, and buildings that are embedded with sensors, software, and other technologies to connect and exchange data.
???The combination of generative AI and IoT has enormous potential for creating new products and services, automating tasks, and improving efficiency. For example, generative AI can be used to create virtual prototypes of IoT devices, allowing manufacturers to test and optimize their designs before producing physical prototypes. Generative AI can also be used to generate new IoT data, such as sensor readings, which can be used to train machine learning models to detect anomalies or predict future behavior.
???Another potential application of generative AI and IoT is in creating personalized experiences for users. By analyzing user data collected from IoT devices, such as wearable devices, smart home systems, and connected vehicles, generative AI algorithms can create customized recommendations, alerts, and notifications.
???However, there are also significant challenges associated with the combination of generative AI and IoT, particularly in the areas of security and privacy. As more devices become connected and generate data, there is a greater risk of data breaches and cyber-attacks. It is essential to ensure that data is protected at every stage of its collection, storage, and analysis, and that users have control over their personal information.
???Overall, the combination of generative AI and IoT has enormous potential for transforming various industries, but it is crucial to address the challenges associated with this technology to ensure that it is deployed in a safe and responsible manner.
Prompt: {{{Actual Case Studies of Generative AI and Industrial IoT}}}
???There are several real-world examples of how generative AI and Industrial IoT (IIoT) are being used together to improve various industrial processes. Here are a few case studies:
西门子 : Siemens has been using generative AI to design and optimize parts for gas turbines. By using generative AI algorithms to create thousands of design options, Siemens has been able to reduce the design process from several months to just a few weeks, while also improving performance and reducing material usage.
通用电气 : General Electric has been using IIoT sensors to collect data from its aircraft engines, and then using generative AI to create predictive maintenance models. These models can predict when maintenance is needed, enabling GE to schedule maintenance proactively and reduce unplanned downtime.
宝马 : BMW is using generative AI and IIoT to optimize its manufacturing processes. By collecting data from sensors on its production lines, BMW can use generative AI to create simulations and test different scenarios to identify the most efficient and cost-effective manufacturing processes.
阿西布朗勃法瑞公司（ABB） : ABB, a robotics and automation company, is using generative AI to create customized robot grippers for its customers. By analyzing data about the objects that the robot will be handling, generative AI can design a gripper that is perfectly matched to the object's shape, size, and weight.
???These are just a few examples of how generative AI and IIoT are being used together to improve industrial processes. As these technologies continue to evolve, we can expect to see even more innovative use cases emerge.
?????? I suppose that from now on, thanks to Generative AI, you guys won't need my newsletter on Industrial IoT anymore, or not... Let's find out!
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INSIGHTS & PERSPECTIVES
?????????? ???????? - ???????????????????? ????: ?? ????????-?????????????? ???????? ?????????????? ?????? ???????????????? ???????? ???? ???? ?????????? ??????: ?????????????? ?????? ?????????????? ???????????????? ?????? ?????????????? ???? ?????? ???????? ????????????, ???????????????????? ???? ?????????????????? ???????????????? ???? ?????????????? ???????? ???????????????? ???????? ??????????????????. ?????? |?Via?World Economic Forum ?| January 2023
??A?Generative Pretrained Transformer?(GPT) is a type of large language model (LLM) that uses deep learning to generate human-like text.
??They are called "generative" because they can generate new text based on the input they receive, "pretrained" because they are trained on a large corpus of text data before being fine-tuned for specific tasks, and "transformers" because they use a?transformer?based neural network architecture to process input text and generate output text.
??While generative AI has people excited about a new wave of creativity, there are concerns about the impact of these models on society:
??Only when solid checks and balances are in place can there be a more thoughtful, beneficial expansion of generative AI technologies / products.
Video:?https://lnkd.in/eviUCNkj
Source:?https://bit.ly/3JDXlbd
#iot ?#ai ?#aiot ?#generativeai ?#gpt ?#largelanguagemodel ?#llm ?#gamechanger ?#investement ?#vc ?#davos ?#wef
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Benefits of Generative AI in manufacturing?!
By Daniel Kuepper , Global co-lead Manufacturing & Supply Chain | 波士顿谘询公司 Managing Director & Senior Partner | March 17, 2023
??The announcements of?OpenAI ?on GPT-4 earlier this week inspired many of us. And we reflected a bit on what this means for a potential application within manufacturing and along the supply chain.
??And yes, there are several areas where Generative AI can be deployed. Take the generation of synthetic training data as an example that can reduce start-up times for advanced robots.
Swipe to the right to find our perspective. And please, like and/or comment and share your views!
Thanks to my colleagues?Dr. Kai-Frederic Seitz ,?Dr. Tilman Buchner ,?Martin Kleinhans ?for supporting with this initial view.
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A New Era of Generative AI for Everyone
The technology underpinning ChatGPT will transform work and reinvent business | Via 埃森哲 | March 22, 2023
Interested in Generative AI and how it impacts business, how we work? Confused about Generative AI vs ChatGPT AI vs Foundation and Large Language Models?*
Read the new report 埃森哲 wrote, hot off the press, to learn more about all of this and what you can do now.
??The technology underpinning ChatGPT will transform work and reinvent business.
??Advances in language-based AI – the technology that powers applications like ChatGPT – are ushering in a new era for?Total Enterprise Reinvention .
??Everything from science to business to society itself will be transformed. The positive impact on human creativity and productivity will be massive.
??Companies will need to radically rethink how work gets done. The focus must be on evolving operations and training people as much as on technology.
??To capitalize, companies need a strong digital core and investments in people to reap the value of AI in a responsible way.
*Note: Generative AI refers to a class of AI models that can generate new content, while ChatGPT is a specific type of generative AI model that is designed for NLP tasks. Foundation and Large Language Models are the massive datasets and pre-trained models that power many modern AI applications, including ChatGPT. All of these technologies have the potential to impact business and how we work in significant ways.
Source: https://accntu.re/3FResVE
#iot ?#ai ?#aiot ?#generativeai ?#chatgpt #gpt #foundation ?#largelanguagemodel ?#llm #business #work #science #society #creativity #productivity #operations #training #investment #people #digital
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6 Applications of Generative AI in Industrials
From infrastructure design to materials discovery, we look at 6 ways industrials companies can leverage generative AI — and the vendors building tech solutions in each area | Via CB Insights | March 22, 2023
??Generative AI?— which refers to AI technologies that generate entirely new content, from lines of code to images to human-like speech — is kindling excitement across manufacturing, automotive, and other industrial sectors.
??The tech is already delivering time and cost savings in a range of business functions, from R&D to product design. For instance, generative AI could reduce design timelines by up to 90% for infrastructure projects and slash raw material use by upwards of 95% in industrial design.?
??Industrials incumbents are moving quickly to take advantage.? Hyundai Assan , for instance, has used? 欧特克 ’s generative design software to figure out how to efficiently make parts for new vehicle modalities.? IBM , meanwhile, is using generative AI to identify and test computer chip materials.?
??Here are 6 industrials applications where generative AI can accelerate product development and scale critical work:?
Source: https://bit.ly/42E1ioZ
#iot ?#ai ?#aiot ?#generativeai ?#gpt ?#largelanguagemodel ?#llm #manufacturing #automotive #industrial #equipment #randd #productdesign
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MARKET MAP: GENERATIVE AI COMPANIES WITH >$5MM RAISED (as of March 2023) | By Kelvin Mu | March 20, 2013
Higher-res downloadable PDF:?https://lnkd.in/gT3ur8cx
??This list includes private, non-exited, generative AI companies with over $5MM USD of total fundraising (as disclosed by PitchBook ).
??The total amount raised is $17B. This is likely extremely understated for two reasons. (1) 微软 didn't disclose their latest round in OpenAI so the official amount recorded here is only $1B (2) many financing rounds are undisclosed. The actual amount is likely 2-3x higher.
??There are nearly 300 companies in this market map, but I'm missing others. If you are a generative AI company with over $5MM of fundraising, please comment below and I'll try to get you added for the next iteration.
领英推荐
??I have not included chip startups such as Cerebras, Graphcore although they are obviously important players to generative AI as well.
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?????????? ???????????????????? ???? ?????? ??????: ?? ???????????????????? ???????? ???????????????????????? ???????????? ??????????????: ?????????????? ?????? ?????????????? ???????????????? ???? ???????????????????? ???? ???????????????????????? ???? ???????????? ?????????? ????????????????. ?????? |?Via?IoT Analytics ?| March 14, 2023
??According to?new research?from?IoT Analytics , most generative AI applications are at a very early stage, with IoT-related use cases currently not in focus.
??Code generation for IoT, robotics control, and social IoT devices are some of the most promising IoT-related applications of generative AI.
?????? ???? ??????????????
??Generative AI and large language models (LLL) are receiving serious attention right now.
??The IoT community is yet to produce a compelling combination of generative AI and IoT.
??Whoever comes up with the first convincing application may generate a first-mover advantage.
Source:?https://bit.ly/3LJYktb
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???????????? ??????????????: ?????? ???????????? ???? ???????????????????? ???? ?????? ?????????????????????? (??????): ??????????????, ?????????? ????????, ???? ???????? ?????? ??????????????????; ???????????????????? ???????? ?????? ???????????????????? ???? ?????? ?????? ???????? ??????????????????????????. ?????? |?Via?Gartner ?- January, 2023
??Venture capital firms have invested over $1.7 billion in generative AI solutions over the last three years, with AI-enabled drug discovery and AI software coding receiving the most funding.
??Generative AI can explore many possible designs of an object to find the right or most suitable match.
??It not only augments and accelerates design in many fields, it also has the potential to “invent” novel designs or objects that humans may have missed otherwise.
???????? ???????????????? ?????? ?????????? ?????? ???????????????????? ????
??Generative AI in drug design
??Generative AI in material science
??Generative AI in chip design
??Generative AI in synthetic data
??Generative design of parts
Source:?https://gtnr.it/3TwUlBT
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???????????????????? ???? ???? ????????: ?????? ?????????? ???????? ?????????????? ?????????? ???????????? ???????? ????????????????: ???????????????????? ???? ?????? ?????????? ???????????????????? ???????????? ?????? ???????????????? ?????? ???? ????????, ???????????? ?????????????????? ???????????????????? ???? ?? ?????? ??????????, ???????????????? ?????????????????????? ?????????????????????? ????????, ?????? ???????????????? ???????????????? ???????????????????????? ???? ???????????????????????? ??????????. ?????? |?Via?McKinsey & Company ?| December 2022
Again, by?ChatGPT ?"itself":
??The rise of generative AI has the potential to be a major game-changer for businesses.
??This technology, which allows for the creation of original content by learning from existing data, has the power to revolutionize industries and transform the way companies operate.
??By enabling the automation of many tasks that were previously done by humans, generative AI has the potential to increase efficiency and productivity, reduce costs, and open up new opportunities for growth.
??As such, businesses that are able to effectively leverage the technology are likely to gain a significant competitive advantage.
???????????????? ???????? ????????????
?????????? ???????????? ?????? ???? ?????? ?????????? ???????? ???? ??????????????, ?????? ????’???? ?????????????? ???????????? ?????? ?????????? ?????????? ???? ???????????????????????? ???????????? ??????????????????, ?????????????????? ?????? ?????????????????? (??????????????):
???????????????????? ?????? ??????????—crafting personalized marketing, social media, and technical sales content (including text, images, and video); creating assistants aligned to specific businesses, such as retail
??????????????????????—generating task lists for efficient execution of a given activity
??????/??????????????????????—writing, documenting, and reviewing code
?????????? ?????? ??????????—answering complex questions, pulling from vast amounts of legal documentation, and drafting and reviewing annual reports
????&??—accelerating drug discovery through better understanding of diseases and discovery of chemical structures
Source:?https://mck.co/3JZ1Kqz
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MAD LANDSCAPE 2023 | MACHINE LEARNING, AI & DATA: Top 10 Trends
By Matt Turck , VC FirstMark | Data Driven NYC | March 15, 2023
??Data infrastructure:?
1. Funding grinds to a halt
2. Bundling & consolidation ahead?
3. The Modern Data Stack under pressure?
4. Convergence and Simplification
??ML/AI:
5. AI goes mainstream (and multimodal)
6. Funding: In AI, it’s party like it’s 1999
7. The new political economy of AI: Big Tech vs AGI Research Labs?
8. New startup opportunities: GenAI SaaS and LLMOps
9. The inevitable backlash: AI ethics & safety
10. The “AI Wars” reach a new level of intensity
Source: https://bit.ly/3FStvP8
#iot ?#ai ?#aiot #ml #data ?#generativeai #genai #saas #llm #ops #landscape #2023trends #mainstream #funding
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Bio:?Fabio Bottacci ?is a relationship builder, creative problem solver and strategic thinker. Senior industrial executive, he acquired a solid background in large multinational organizations across Brazil, US, and Western Europe. He is known for his ability to deliver results despite ambiguity and obstacles, to build bridges between people and to manage conflict and negotiations.
He began his career at?Accenture Italia , strategy practice, while attending MBA courses. He then moved to Brazil, where he consistently proved, during more than 20 years of professional experience, strong client's network, industry knowledge and business development expertise in the oil and gas, automotive and energy/utilities verticals.
Since 2015, he has been the founder & CEO of?VINCI Digital - Industrial IoT Strategic Advisory , being recognized internationally as a thought leader by well-known organization, such as the?Wor ld Economic Forum ,?IoT Solution World Congress ,?BNDES , etc., and helping startups, SME, and big corporations to thrive within the actual digital transformation environment, by developing new business models, and delivering actual results/ROI in months, not years.
Director Marketing & Sales
1 年The case studies of GPT where it designed parts for some companies, woukd that become an open data for other users if they searched for similar information ?
Director Marketing & Sales
1 年If one desires GPT to extract results from proprietary material and suggest the right solution to a user to resolve problems of a proprietary system, how would one use this GPT ? Not exposing this info to others regarding the results it achieved about proprietary system and for the specific user ? Would that require some retraining?