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Data volumes are exploding across organizations of all types. Research firm IDC projects the amount of global data to more than double between now and 2026, with enterprise data leading that growth — increasing twice as fast as consumer data. Accordingly, it is a business imperative to store, protect, and provide access to this growing volume of data, while finding new ways to derive value from it.

The surge in data volumes is driven by multiple factors: Historical data that companies have been collecting for years continues to pile up. New data types are proliferating, such as IoT (Internet of Things) sensor data, operational technology (OT) data, and customer experience data. Core business functions, such as supply chain, are becoming increasingly more data driven.

Weeds are one of the most “tedious, time-consuming and challenging” elements of farming, Carbon Robotics told Fox Business via email.

The LaserWeeder can eliminate over 200,000 weeds per hour and offer up to 80% cost savings in weed control.

Carbon Robotics CEO and founder Paul Mikesell “knows farmers and has a lot of friends who are farmers,” he said.

The winners of the Non-Profit Organisation Awards 2023 by Acquisition International have just been announced and The Millennium Project has been awarded for Excellence in Innovation – USA!

The Non-Profit Organisation Awards aim to reward Non-profit organizations that globaly that play a monumental role in solving some of our biggest global challenges. The awards reward commitment, innovation, and determination of the best NPOs from across the world by selecting the most innovative, creative and compassionate NPOs, and provide a platform for NPOs to demonstrate that they are a true leader within the non-profit sphere.

The approach for nominations includes gathering and evaluating the nominees, research and judging on various criteria, including client dedication, innovation, business growth, longevity, online reputation, client feedback and business performance, and announcement of the winners.

Security and risk teams are already overwhelmed protecting their SaaS estate (which has now become the operating system of business) from common vulnerabilities such as misconfigurations and over permissioned users. This leaves little bandwidth to assess the AI tool threat landscape, unsanctioned AI tools currently in use, and the implications for SaaS security.

With threats emerging outside and inside organizations, CISOs and their teams must understand the most relevant AI tool risks to SaaS systems — and how to mitigate them.

Data and analytics have played a key role in all four dimensions of digital transformation—that is, customers, employees, products and operations—by helping businesses understand these functions and by offering actionable insights. These insights have been necessary to enable timely interventions to optimize operations or offer excellent customer experience by continuously innovating products and services.

Likewise, with generative AI becoming more widely available through ChatGPT from OpenAI and BARD from Google, among other products, the power of AI can help break innovation barriers and transform businesses. Generative AI is a subset of AI capable of creating new content in the form of text, code, voice, images, videos and processes in response to user prompts.

AI and analytics solutions powered by generative AI will likely have significant impact on all four dimensions of digital transformation to be innovative and accelerate the journey.

Malls are becoming places for public libraries, animal shelters, basketball courts and entertainment centers.


Across the United States, some malls are undergoing big changes. Businesses such as animal shelters, trampoline parks and movie theaters are filling the spaces that have been left empty in recent years. NBC News’ Brian Cheung has the story.

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SpaceX is revolutionizing the Internet industry with its Starlink broadband satellite network. As of today, the company operates a constellation of around 4,265 Starlink satellites in Low Earth Orbit (LEO) that provide high-speed internet to over 1.5 million subscribers globally. SpaceX is launching Starlink satellites every month to continue expanding service coverage, with plans to launch a total of 12,000 satellites. Besides providing internet to homes and businesses, Starlink beams service directly to user antennas installed on vehicles in motion, like RVs, cruise ships, and aircraft.

In the early days of satellite internet, Geostationary Earth Orbit (GEO) satellites were the norm for aviation. These GEO satellites, positioned at an altitude of approximately 36,000 kilometers above the Earth’s surface, provided coverage to large regions but have limitations in terms of speed and latency – making it hard to livestream or have video calls in-flight. However, everything changed when SpaceX set its sights on LEO and launched thousands of satellites. One of the key advantages of Starlink’s satellites is the ability to provide faster internet speeds because they operate at much lower altitudes of around 550 kilometers. With traditional GEO satellites, the signal had to travel a considerable distance to reach the satellite and then make the round trip back to Earth, resulting in noticeable lag and latency average of around 600ms (milliseconds). In contrast, Starlink’s LEO satellites are positioned much closer to the planet, reducing the distance the signal travels.

Data science has been around for a long time. But the failure rates of big data projects and AI projects remain disturbingly high. And despite the hype, companies have yet to cite the contributions of data science to their bottom lines.

Why is this the case? In many companies, data scientists are not engaging in enough of softer, but more difficult, work, including gaining a deep understanding of business problems; building the trust of decision makers; explaining results in simple, powerful ways; and working patiently to address concerns among those impacted.

Managers must do four things to get more from their data science programs? First, clarify your business objectives and measure progress toward them. Second, hire data scientists best suited to the problems you face and immerse them in the day-in, day-out work of your organization. Third, demand that data scientists take end-to-end accountability for their work. Finally, insist that data scientists teach others, both inside their departments and across the company.

Who’s afraid of the big bad bots? A lot of people, it seems. The number of high-profile names that have now made public pronouncements or signed open letters warning of the catastrophic dangers of artificial intelligence is striking.

Hundreds of scientists, business leaders, and policymakers have spoken up, from deep learning pioneers Geoffrey Hinton and Yoshua Bengio to the CEOs of top AI firms, such as Sam Altman and Demis Hassabis, to the California congressman Ted Lieu and the former president of Estonia Kersti Kaljulaid.

Companies are integrating AI into their operations so quickly that job losses are likely to mount before the gains arrive. White-collar workers might be especially vulnerable in the short-term. The speed of this adoption presents an opportunity for companies to step up their pace of innovation, however — and if enough companies to go on offensive, then we won’t have to worry about AI unemployment. Adopting a bias for boldness and a startup mentality will help companies find the agility to make the most of this moment, and protect jobs as a result.

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Investing in innovation — not cutting costs — will position companies to thrive in the long run.

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