Starlink has landed what is likely its biggest partnership yet as it signed recently to provide a prominent company with internet service.
Large language models have emerged as a transformative technology and have revolutionized AI with their ability to generate human-like text with seemingly unprecedented fluency and apparent comprehension. Trained on vast datasets of human-generated text, LLMs have unlocked innovations across industries, from content creation and language translation to data analytics and code generation. Recent developments, like OpenAI’s GPT-4o, showcase multimodal capabilities, processing text, vision, and audio inputs in a single neural network.
Despite their potential for driving productivity and enabling new forms of human-machine collaboration, LLMs are still in their nascent stage. They face limitations such as factual inaccuracies, biases inherited from training data, lack of common-sense reasoning, and data privacy concerns. Techniques like retrieval augmented generation aim to ground LLM knowledge and improve accuracy.
To explore these issues, I spoke with Amir Feizpour, CEO and founder of AI Science, an expert-in-the-loop business workflow automation platform. We discussed the transformative impacts, applications, risks, and challenges of LLMs across different sectors, as well as the implications for startups in this space.
In a recent study led by the University of Liège researchers delved into the intersection of the fields of entrepreneurship and neuroscience, looking specifically at the cognitive flexibility of habitual entrepreneurs—those who repeatedly launch new businesses—compared to less experienced entrepreneurs and managers.
It reads. It talks. It collates mountains of data and recommends business decisions. Today’s artificial intelligence might seem more human than ever. However, AI still has several critical shortcomings.
Those who rush to leverage AI’s power without adequate preparation face difficult blowback, scandals, and could provoke harsh regulatory measures. However, those who have a balanced, informed view on the risks and benefits of AI, and who, with care and knowledge, avoid either complacent optimism or defeatist pessimism, can harness AI’s potential, and tap into an incredible variety of services of an ever-improving quality.
These are some words from the introduction of the new book, “Taming the machine: ethically harness the power of AI”, whose author, Nell Watson, joins us in this episode.
McDonald’s (MCD) will put an end to its AI drive-thru partnership with IBM (IBM) in late July as many customer complaints over botched orders began to mount. The fast-food chain does have plans to continue implementing AI into its business model down the line.
The Morning Brief Anchors Brad Smith and Seana Smith break down the latest developments for McDonald’s and what it means for the company moving forward.
Continue reading “McDonald’s will end AI drive-through partnership with IBM” »
In a somewhat unexpected turn of events, the ongoing controversy surrounding Photoshop and Substance 3D developer Adobe has extended beyond negative social media comments and Twitter Community Notes and into real life, with the company getting sued by the US government on the grounds of the former’s questionable business practices.
The federal court complaint, filed by the Department of Justice following a referral from the Federal Trade Commission, alleges that Adobe has been harming its users by enrolling them in its default subscription plan without clearly disclosing important terms regarding the cancellation process, effectively making one’s attempt to cancel their subscription a massive pain in the back.
Researchers in the Netherlands are developing ‘virtually painless’ injections without needles in what they hope is a breakthrough that will ease fear and encourage vaccinations.
#News #Reuters #BubbleGun #NeedleFree #Vaccine.
Continue reading “Dutch develop no-pain needle-free injections” »
Salesforce recently announced that it has introduced more than 50 AI-powered tools among its workforce and reported that these tools have collectively saved all of its employees in excess of 50,000 hours—or 24 years’ worth—of working time in just three months.
As a company, Salesforce serves as an especially compelling case study for the impact of AI on work—not only because the company tests tools on their own workforce, but because so many others rely on Salesforce’s products to do their jobs each day. Simply put: Salesforce is in the business of work.
Salesforce has more than 70,000 employees worldwide—a 30% increase since 2020. And the software giant builds the products that are used by employees at some 150,000 workplaces, from small businesses to Fortune 500 companies; from sales and customer service teams to marketing and tech teams.
