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Category: business – Page 48

PARIS – Elon Musk’s SpaceX is no longer absorbing the cost of the Starlink antennas that it sells with its satellite internet service, a company executive said on Wednesday, a key step to the company improving its profitability.

“We were subsidizing terminals but we’ve been iterating on our terminal production so much that we’re no longer subsidizing terminals, which is a good place to be,” Jonathan Hofeller, SpaceX vice president of Starlink and commercial sales, said during a panel at the World Satellite Business Week conference.

SpaceX sells consumer Starlink antennas, also known as user terminals, for $599 each. For more demanding Starlink customers – such as mobile, maritime, or aviation users – SpaceX sells antennas with its service in a range from $2,500 to $150,000 each.

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Companies are struggling with where to start with generative AI. The authors’ case studies, based on their growing global community of over 3,000 GenAI practitioners, point to a new category of work, more precise and actionable than “knowledge work.” They call it WINS Work — the places where tasks, functions, possibly your entire company or industry — are dependent on the manipulation and interpretation of Words, Images, Numbers, and Sounds (WINS). This framework can help leaders identify how vulnerable their business is to changes from this new technology and plan their response.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.362921 data-title= Where Should Your Company Start with GenAI? data-url=/2023/09/where-should-your-company-start-with-genai data-topic= AI and machine learning data-authors= Paul Baier; Jimmy Hexter; John J. Sviokla data-content-type= Digital Article data-content-image=/resources/images/article_assets/2023/09/Sep23_09_AlexWilliam-383x215.jpg data-summary=

Understand where your company stands — and what it needs to do.

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Though artificial intelligence has been making inroads into the enterprise, the rise of generative AI is accelerating the pace of adoption. It’s time for enterprise CXOs to consider building systems of intelligence that complement systems of record and systems of engagement.

In the last two decades, enterprises have invested in building solid foundations for managing data and information. Relational databases such as Oracle and Microsoft SQL Server became the cornerstone of information systems. Built on this foundation were customer relationship management, human resources management, supply chain management and other line of business applications that quickly became the digital backbone of… More.

This context, when combined with advanced prompt engineering, helps enterprises build intelligent AI-based assistants on the lines of Microsoft Copilot or Google Duet AI.

The foundation models become the core of systems of intelligence. The contextual information generated via semantic search is fed to these generative AI models, which deliver rich insights and accurate information to users. The use cases aligned with SOI go beyond typical chatbots. Different teams within an organization will use them to handle a range of scenarios, from marketing to sales forecasting.

Continue reading “The Time Is Now: Why Enterprises Should Invest In Systems Of Intelligence” | >

Fifty years ago, the average business transaction was pretty straightforward. Shoppers handed purchases directly to cashiers, business partners shook hands in person, and people brought malfunctioning machines to a repair shop across the street. The proximity of all participating parties meant that both customers and businesses could verify authority and authenticity with their own eyes.

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Rob Tillman, CIO of Copy Chief, has 20+ years transforming businesses with a human-centric innovation model deployed across diverse sectors.

In today’s fast-paced digital age, the term “innovation” is frequently thrown around in boardrooms, tech conferences and startup pitches. It’s often hailed as the driving force behind progress and the competitive edge for businesses. But have we ever paused to truly understand what innovation means at its core?

It’s not just about creating groundbreaking technologies or pioneering novel solutions. At its heart, innovation is about empowering humans.

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Under the proposal, developing face recognition and other “high risk” applications of AI would also require a government license. To obtain one, companies would have to test AI models for potential harm before deployment, disclose instances when things go wrong after launch, and allow audits of AI models by an independent third party.

The framework also proposes that companies should publicly disclose details of the training data used to create an AI model and that people harmed by AI get a right to bring the company that created it to court.

The senators’ suggestions could be influential in the days and weeks ahead as debates intensify in Washington over how to regulate AI. Early next week, Blumenthal and Hawley will oversee a Senate subcommittee hearing about how to meaningfully hold businesses and governments accountable when they deploy AI systems that cause people harm or violate their rights. Microsoft president Brad Smith and the chief scientist of chipmaker Nvidia, William Dally, are due to testify.

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GPT-4, PaLM, Claude, Bard, LaMDA, Chinchilla, Sparrow – the list of large-language models on the market continues to grow. But behind their remarkable capabilities, users are discovering substantial costs. While LLMs offer tremendous potential, understanding their economic implications is crucial for businesses and individuals considering their adoption.

While LLMs offer tremendous potential, understanding their economic implications is crucial for businesses and individuals considering their adoption.

First, building and training LLMs is expensive. It requires thousands of Graphics Processing Units, or GPUs, offering the parallel processing power needed to handle the massive datasets these models learn from. The cost of the GPUs, alone, can amount to millions of dollars. According to a technical overview of OpenAI’s GPT-3 language model, training required at least $5 million worth of GPUs.

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Bobbi is SVP, Software Engineering at Loopio. She is a technology leader with over 25 years of diverse experience in the industry.

AI and emerging technologies under the AI umbrella—like generative pre-trained transformers (GPT)—are reshaping the business world. These technologies are fostering greater organizational efficiencies and innovations and are quickly becoming crucial for companies of all sizes.

The ability to automate processes and tasks opens up a plethora of new opportunities for organizations. When automation can scale with an organization, this can completely transform day-to-day operations. In this article, I’ll look at three ways that engineering organizations in particular can use AI to transform their organizational efficiencies, organizational structure and software practices and processes.

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The world’s largest democracy is poised to transform itself and the world, embracing AI on an enormous scale.

Speaking with the press Friday in Bengaluru, in the context of announcements from two of India’s largest conglomerates, Reliance Industries Limited and Tata Group, NVIDIA founder and CEO Jensen Huang detailed plans to bring AI technology and skills to address the world’s most populous nation’s greatest challenges.

“I think this is going to be one of the largest AI markets in the world,” said Huang, who was wrapping up a week of high-level meetings across the nation, including with Prime Minister Narendra Modi, leading AI researchers, top business leaders, members of the press and the country’s 4,000-some NVIDIA employees.

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NEW YORK—()— Paige, a technology disruptor in healthcare, has joined forces with Microsoft in the fight against cancer, making headway in their collaboration to transform cancer diagnosis and patient care by building the world’s largest image-based artificial intelligence (AI) models for digital pathology and oncology.

“Unleashing the power of AI is a game changer in advancing healthcare to improve lives.” Tweet this

Paige, a global leader in end-to-end digital pathology solutions and clinical AI, developed the first Large Foundation Model using over one billion images from half a million pathology slides across multiple cancer types. Paige is developing with Microsoft a new AI model that is orders-of-magnitude larger than any other image-based AI model existing today, configured with billions of parameters. This model assists in capturing the subtle complexities of cancer and serves as the cornerstone for the next generation of clinical applications and computational biomarkers that push the boundaries of oncology and pathology.

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