Discover how AI is used today and how it will augment human experience in the future
Climate risks threaten insurers' profitability and financial stability. See how insurers can adapt.
Discover how AI is used today and how it will augment human experience in the future
Climate risks threaten insurers' profitability and financial stability. See how insurers can adapt.
Entre as organizações que já adotaram a GenAI, os benefícios são notáveis. Mas obter ROI ainda é um desafio que requer atenção dos líderes de negócios A inteligência artificial generativa (GenAI) se firmou como uma força propulsora no mundo corporativo, transformando a interação entre humanos e tecnologia de maneira inédita.
SASクラウドエコノミクスおよびビジネスバリューチームのSpiros PotamitisとFrancesco Raininiがこの記事の執筆に協力しました。2023年11月16日に公開された英語の記事を翻訳しております。 クラウド コンピューティングは数え切れないほど多くの業界のバックボーンとなり、組織が分析、機械学習、AI の力を活用して洞察とイノベーションを実現できるよう支援しています。 クラウドコンピューティングの急速な拡大により、クラウドは大きな二酸化炭素排出量を生み出すようになりました。背景として、クラウドは世界の二酸化炭素排出量の最大 4%を占めると計算されており、これは航空業界が排出する量よりも多いと考えられています。 これに対して何ができるでしょうか? オンプレミスの展開についてはどうでしょうか? クラウドとオンプレミスの議論に関しては、大手市場調査会社である IDC は、コンピューティングリソースの集約効率が高いため、オンプレミスと比較してクラウドの方が環境に優しい選択肢であると主張しています。したがって、AI と分析のワークロードをクラウドに移行するのが環境にとって最善の方法であると言われています。 クラウドでの効率を向上できる組織が増えれば、累積的な影響を考慮すると、小さな改善でも大きな違いを生む可能性があります。 SAS® Viya®と環境 SAS Viya は、 5 年間で最大 50 トンの CO2eの炭素排出量を削減する可能性があります。成長した木がこの量のCO2eを吸収するには 4,513 年かかると言われています。 カーボンフットプリントを楽しく探る 様々な要点を総合的に考慮し、Viya の潜在的な環境的利点を計算するために、私たちはGreen Algorithm Calculator を使用しました。これは、計算ワークロードの二酸化炭素排出量を推定して報告するツールです。計算を完了するために、さまざまな Azure Cloud アーキテクチャにわたる 1,500 を超えるテストを含むFuturum ベンチマーク調査の数値を使用しました。この調査では、Viya がオープンソースや主要な代替手段と比較して平均で 30 倍高速であることが示されています。 私たちは、大規模な組織に典型的なインフラストラクチャと分析のワークロードを想定しました。同時に、Futurum の調査で使用された技術的設定を反映しているため、計算に自信を持ってメリットの数値を適用できます。 グリーンアルゴリズム 計算機を使用して計算するには、次の手順に従います。 実行時間から始めます。50 人のデータ
The search to maximize our own productivity is never-ending. We all want to be more efficient in our work and carve out more time with loved ones. As you assess data and AI technology to automate processes and maximize efficiency, you may wonder if it’s truly possible for you or
El lavado de dinero se continúa posicionando como una de las principales problemáticas ilegales, por su asociación con actividades ilícitas y crímenes financieros. Un reporte de Global Financial Integraty, titulado “Crímenes Financieros en América Latina y el Caribe: entendiendo los desafíos de los países y diseñando respuestas técnicas efectivas”, estimó
Making informed decisions quickly is more critical than ever. As markets shift and customer expectations evolve, companies need tools to process vast data and turn insights into actionable strategies. That’s where SAS Decision Builder comes in, now available through Microsoft Fabric's public preview announced at Microsoft Ignite. With SAS Decision
The global hype cycle of AI, driven in large part by ChatGPT, is dying down and real-world artificial intelligence (AI) adoption and application are taking hold. Early adopters are reaping rewards, and AI leaders are driving significant change in their business models. Banking as a sector was quick to grasp
Insurers are racing to adopt GenAI, despite concerns. See where the industry is headed.
Fearmongers would have you believe that AI will replace us, but I truly believe there has never been a better time in history to be a developer. With the advance of artificial intelligence into generative AI (GenAI) and enhanced computing power, we stand on the brink of a new era
Data scarcity, privacy and bias are just a few reasons why synthetic data is becoming increasingly important. In this Q&A, Brett Wujek, Senior Manager of Product Strategy at SAS, explains why synthetic data will redefine data management and speed up the production of AI and machine learning models while cutting
Synthetic data generation, as its name suggests, is one component of generative AI. With this technology, marketers can generate artificial data sets that share the attributes and characteristics of real customer data. As marketers continue to expand their use of both traditional AI and GenAI, synthetic data generation reduces the
Decisores em diversas indústrias já sabem que a implantação de grandes projetos de analytics, IA e dados tem se tornado cada vez mais estratégica para o sucesso dos negócios. Porém, a execução destas iniciativas requer atenção em pontos cruciais, que vão desde a identificação dos objetivos até a adoção e
As we move into 2025, AI continues to transform industries in unprecedented ways, driving efficiency, innovation, and productivity. But with this rapid advancement come critical ethical questions. How can we ensure that AI systems protect the rights and well-being of individuals? Manufacturing and agriculture are two essential industries where answering
En la era de la transformación digital, la velocidad, la escalabilidad y la rentabilidad no son solo indicadores de desempeño; son factores decisivos que permiten a las empresas mantenerse competitivas. Hoy, en SAS, nos enorgullecemos de ver cómo nuestra plataforma de IA y analítica, SAS Viya, no solo cumple con
Cada vez más los datos se han convertido en el corazón de todas las operaciones empresariales. Sin embargo, gestionarlos de manera eficiente y convertirlos en información valiosa sigue siendo un desafío. Una buena gestión de datos es esencial para garantizar resultados confiables, éticos y libres de sesgos; que a su
Halloween is one of my favorite times of the year – I'm a Halloween enthusiast. It’s a time for spine-tingling thrills, haunted tales and lots of candy corn. But there’s one fear lurking in the shadows that sends shivers down the spines of data scientists, IT leaders and executives alike,
Según Google Trends en los últimos 5 años las búsquedas “ansiedad por IA” y “estrés por IA” han aumentado en un 100%. De hecho, terapeutas de todo el mundo enfrentan un nuevo tipo de cliente que llega a su consulta: pacientes con ansiedad a causa de esta tecnología. A medida
Generative AI (GenAI) is here to stay – there’s no question about it. A recent SAS survey of 1,600 organizations found that 54% have begun implementing It, and 86% plan to invest in it within the next financial year. As organizations integrate AI into their workflows, a critical question arises:
"Generative AI (GenAI) initiatives should support broader public goals and needs," says SAS' Ensley Tan. While governments recognize GenAI's potential to improve operational efficiency and citizen experience, there is more to it than setting up projects and expecting them to work. Tan, SAS Asia-Pacific Lead for Public Sector Consulting, said public
Investment in AI is an obvious target for the insurance sector. Insurers have always been interested in technology that helps detect and prevent fraud and improve underwriting efficiency while speeding processes and reducing – or at least not increasing – costs. But what is the reality in this highly regulated
Dans le paysage technologique actuel, les données synthétiques, nouveau sous ensemble de l’IA générative, apportent de nouvelles pistes de réflexion pour la création des modèles d'intelligence artificielle. Contrairement aux données traditionnelles, pouvant être limitées par des contraintes de biais, de quantité, ou encore des contraintes de confidentialité et de conformité,
Remember the first time you held a smartphone in your hand? It wasn’t just a fancy phone – it was the beginning of a revolution. Before smartphones, we used separate calls, cameras, emails, and navigation devices. But almost overnight, this gadget transformed everything: how we communicate, consume media, work and
Everyone has heard it: Your organization needs to be more productive. But how? Businesses are constantly challenged with adopting AI technology, managing rising costs and closing talent gaps. While AI can boost performance, the need for faster, more performant models is often stymied by inefficient handoffs between key roles within
AI is no longer a futuristic concept – it’s a mainstay in our daily lives, both personally and professionally. In the business world, AI is revolutionizing workflows, driving efficiency and speeding up processes. However, as organizations rush to benefit from this modern technology, they must prioritize the ethical and transparent
Data science continues to be a pivotal force driving innovation across industries. From enhancing customer experiences to optimizing operational efficiencies, the role of data science is expanding, bringing with it new challenges and opportunities. This article explores the emerging trends and technologies that are shaping the future of data science
A woman arrives at the emergency room with chest pain. She immediately receives an x-ray. While the radiologist looks at the image, her AI assistant flags anomalies in the patient’s lungs – invisible without the technology. The chest pain turns out to be benign, but sophisticated imaging reveals early-stage lung
Everyone is talking about artificial intelligence (AI) for a good reason. It’s already revolutionizing the world as we know it. And governments are well-poised to use AI to improve services and operations. But we can expect the AI conversation to shift into 2025. Attend any conference of government leaders, and
El futuro de la innovación empresarial no solo está llegando, está ocurriendo ahora. La reciente clausura del evento SAS Innovate On Tour 2024 en la Ciudad de México dejó claro que la inteligencia artificial generativa (GenAI) y la analítica avanzada están cambiando radicalmente la manera en que las organizaciones operan
We know that building trust in technology is a big deal. It’s no longer enough for AI to just work – we need to understand how it works, what it is doing and whether it’s performing as expected. That’s where model cards come in. If you remember from our previous
Model cards have been around for a few years now and while their purpose is clear – to increase machine learning transparency and to create a way to communicate usage, ethics-informed evaluation, and limitations – they're still evolving. Many companies have tried their hand at creating their own version of