RE:RE:RE:RE:jmo financing MG has clearly stated they have a good cash position and ongoing revenue streams from all verticals to surain them going forward as they scale up both AnalyticsGPT & Marketing
Verticals:
Telehealth
EV Charging
AI / NexaSMART / AnalyticsGPT
Must mention re : AnalyticsGPT
(I think DM's "Query Analyzer" is a company maker all by itself.
The elimination of the need for a company to hire a so-called Prompt Engineer to design a steering mechanism to implement their Web3 strategy and enable them to hopefully leverage the opportunity that GPT Models represents
is Pure Gold for DM
https://www.msn.com/en-in/money/topstories/prompt-engineer-is-the-hottest-new-job-see-qualifications-and-salary-details/ar-AA1gECrW
Icing on the Cake is Automated Real-Time Updates providing military grade constant oversight of your query
then add in Discovering the Unknowns makes it Linchpin (Must Have) Tech
+ Speaking of Amazon
TBA / DM already in Talks with
3 Studios about a Restart of their
Highly Lucrative Covid Testing Services on Production Sets
(Timing is Everything for DM:-)
Reminder: DMEVS Charging Stations now Deployed to Hollywood North Production Sets
https://www.vicnews.com/world-news/deal-cut-to-end-146-day-writers-strike-crippling-hollywood-4507623
Source of Forbes article below:
https://www.forbes.com/sites/forbestechcouncil/2023/09/25/the-greatest-transformation-since-the-lightbulb-three-ways-generative-ai-will-catalyze-ai-adoption/?sh=624581eb14a4
People worldwide are now knowingly using this technology to create new text, images, audio, video, synthetic data, code and everything in between. From 2023 to 2030, it is anticipated that AI will experience a yearly expansion rate of 37.3%. Consider the GPTs (generative pre-training transformers) that have made the headlines recently and the machine and deep learning tools that have long focused on generative processes.
Perhaps the greatest gifts of generative AI have been its increased accessibility, applied frameworks and quick organizational benefits. The growing awareness around generative AI will undoubtedly serve as the catalyst for small and large enterprises to adopt the technology more widely. However, as with technology in general, being aware of the potential challenges associated with generative AI can help you and your team be prepared to handle these challenges when they arise.
Here are three ways we’ll see generative AI accelerate AI adoption and a few challenges to be on the lookout for.
Increased Accessibility Of AI
For starters, there is a low barrier of entry to using generative AI, which naturally increases the accessibility of the technology for all types of employees in different industries. This democratization of AI will only foster greater innovation and opportunities for companies of all sizes.
Developers and users alike can create low- or no-code platforms that integrate generative AI and speed up software development cycles. That is good news since 35% of companies are embracing AI due to workforce shortages. Beyond coding, generative AI can be leveraged to avoid the steep learning curves tied to new applications and deliver business results right at the outset.
Applied AI Frameworks And Guardrails
By applying frameworks and setting guardrails for AI, companies can accelerate the adoption and ensure the security of this technology, which goes hand in hand. This system provides users with comprehensive guidance on the proper usage of the technology, enabling them to make informed decisions about its application.
Furthermore, the system’s meticulous admin permissions ensure strict control over user actions, preventing misuse or unauthorized usage. By understanding the proverbial "do's and don’ts" of AI and the limitations of its usage, they will be more comfortable with its introduction and day-to-day applications.
This also ensures that the AI is being used in a secure, ethical fashion, which results in a better user experience for not only the user but also the company and its customers. Here are a few ways this works.
• As suggested by Gartner, users must verify and approve all output generated by this technology to ensure accuracy and appropriateness to the topic at hand. As we’re all aware, with any tool, errors can occur. The key here is not getting too comfortable and making sure to validate the output.
• Large language models may exhibit a tendency to generate inaccurate or unexpected outputs. If the generated output doesn't meet expectations, try different prompt formulations or redraft the prompt in alternative ways and resubmit it for improved results.
• There are generative AI tools on the market that provide reasoning and insight into the approach that led it to come up with the provided response. This provides transparency to the user, helps validate the generative AI’s response and brings credibility to the user overseeing this process when bringing an influential suggestion to the table.
Fruits Of Employee-AI Interaction
The more users are made aware of when generative AI works for them and how the technology impacts their performance positively, the more they will buy into, support—and even contribute to—new digital initiatives. Through accurate data collection, streamlined processing and advanced analytics, AI-enabled systems quickly form the backbone of human-led enterprises, impacting different business functions in the following ways.
• Marketing: Generative AI can be leveraged for lead identification, thanks to its ability to identify customer trends in real time. In fact, McKinsey classifies lead identification as a top use case for this technology in marketing.
• Legal: From drafting new contracts and memos and performing comprehensive information discovery across multiple documents to extracting valuable data from documents such as clauses, dates and parties involved, generative AI saves substantial time for legal by eliminating traditionally manual processes.