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Microsoft Corp. (MSFT) continued to point the company toward a generative artificial intelligence (AI) future with the launch Thursday of its first business-focused Surface PCs. Here are the new features you can expect to find in the Surface Pro 10 for Business and Surface Laptop 6 for Business.

The new Surface PCs are driven by Intel Corp. (INTC) Core ultra processors designed to provide powerful and reliable performance for business applications. Microsoft said its Surface Laptop 6 is two times faster than Laptop 5, while the Surface Pro 10 is up to 53% faster than the Pro 9. The enhanced speed and Neural Processing Unit (NPU) technology allow users to benefit from AI tools such as Windows Studio Effects and give business users and developers an opportunity to build their own AI apps and experiences.

Microsoft said the Surface Pro 10 for Business is its most powerful model to date and includes a new Copilot key. The new addition to the Windows keyboard will allow shortcut access to the company's flagship Copilot AI tool. Other improvements to the keyboard include a bold keyset, larger font size, and backlighting to make typing easier, alongside a screen that is 33% brighter, according to the company. Microsoft 365 apps like OneNote and Copilot also will be able to use AI to analyze handwritten notes on the Surface Slim Pen.

For the Surface Pro 10, Microsoft has focused much of its upgrade on an enhanced video calling experience. A new Ultrawide Studio Camera is its best front-facing camera on a Windows 2-in-1 or laptop that features a 114 field of view, captures video in 1440 pixels, and uses AI-powered Windows Studio Effects to ensure presentation quality, Microsoft said. The company also has launched a series of new accessories for users who want an alternative to the traditional mouse. These include custom grips on the Surface Pen and an adaptive hub device that offers three USB ports.

Finally, the new Surface PCs for business have added security features for business users, which include smart card reader technology. Surface users can access the PC with "chip-to-cloud" ID card security for authentication. Surface 10 users can get access to new near-field communication (NFC) reader technology that allows for secure, password-less authentication with NFC security keys.

Microsoft will host a special Windows and Surface AI event on May 20, at which Chief Executive Officer (CEO) Satya Nadella will outline the company's "AI vision for software and hardware. Earlier this week, the company announced that it had hired DeepMind co-founder Mustafa Suleyman as the CEO of its growing AI unit.

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Microsoft's First AI Surface PC: What Does It Offer? - Investopedia

The Financial Times has a new generative AI chatbot called Ask FT that can answer questions its subscribers ask. Similar to generalized AI bots (like ChatGPT, Copilot, or Gemini), users can expect a curated natural language answer to whatever they want to know but with answers derived from the outlets decades of published information rather than sources that are harder to explain or are subject to ongoing legal action. So dont expect it to give you an answer for the best recipe for fettucini alfredo.

When we asked, Who runs Microsofts AI products? the tool returned an up-to-date answer and referenced news that broke this week about Microsoft hiring DeepMind co-founder Mustafa Suleyman as the head of its new AI team:

Mustafa Suleyman currently runs Microsofts consumer-facing AI products and division as the head of Microsoft AI, reporting directly to Satya Nadella [1,2,3]. He was brought in from Inflection AI to expand Microsofts focus on developing generative AI for personal consumer use [1,2,3,4,6].

The bracketed numbers correspond to the FT articles it pulled information from, which it lists beneath the answer. It also provides the time period when these articles were written. In the case of this Microsoft question, it says it pulled information ranging from March 1st, 2023, to March 20th, 2024.

We found inconsistencies with some answers, however. At the time of our testing, the tool included Nikki Haley in its answer to our question about whos currently running for the 2024 US presidential election, even though shed dropped out of the race already.

Screenshot by Emma Roth / The Verge

Its available to a few hundred paid subscribers in the FT Professional tier, which is geared toward business professionals and institutions. Ask FT is currently powered by Claude, the large language model (LLM) developed by Anthropic, but that could change. In an interview with The Verge, FT chief product officer Lindsey Jayne says the outlet is approaching this as model agnostic and seeing which one meets our needs best.

It can provide responses to questions about current events, like how much funding Intel received from the US government under the CHIPS Act, as well as broader queries, like the effect of cryptocurrency on the environment. The tool then gleans the FTs archives and summarizes the relevant information with citations.

Ask FT will also answer questions that require deeper digging into the FTs archives. When asked how YouTube started, it correctly responded that it was founded by Chad Hurley, Steve Chen, and Jawed Karim in February 2005.

We did a whole bunch of testing internally and use that to refine how we instruct the model and how we construct the code, Jayne says. In this first group of 500, we are tracking every question and response, as well as the users feedback.

Last year, we tried a similar tool deployed by the digital outlets owned by the marketing company Foundry, including Macworld, PCWorld, and Tech Advisor. However, at the time it wasnt as useful as Ask FT is; my colleague Mia Sato found it provided inaccurate results to simple questions like when the last iPod Nano was released.

I dont think youd get to be a 135-year-old institution if you arent constantly evolving and meeting these moments, Jayne says. But you have to be smart and not just get on the hype train ... otherwise people just play with it for novelty and then go about their lives.

Most subscribers wont be able to try out the chatbot just yet. Ask FT will remain in beta for now, as the FT continues to test and evaluate it.

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Financial Times tests an AI chatbot trained on decades of its own articles - The Verge

Posted by Yossi Matias, VP Engineering & Research, and Grey Nearing, Research Scientist, Google Research

Floods are the most common natural disaster, and are responsible for roughly $50 billion in annual financial damages worldwide. The rate of flood-related disasters has more than doubled since the year 2000 partly due to climate change. Nearly 1.5 billion people, making up 19% of the worlds population, are exposed to substantial risks from severe flood events. Upgrading early warning systems to make accurate and timely information accessible to these populations can save thousands of lives per year.

Driven by the potential impact of reliable flood forecasting on peoples lives globally, we started our flood forecasting effort in 2017. Through this multi-year journey, we advanced research over the years hand-in-hand with building a real-time operational flood forecasting system that provides alerts on Google Search, Maps, Android notifications and through the Flood Hub. However, in order to scale globally, especially in places where accurate local data is not available, more research advances were required.

In Global prediction of extreme floods in ungauged watersheds, published in Nature, we demonstrate how machine learning (ML) technologies can significantly improve global-scale flood forecasting relative to the current state-of-the-art for countries where flood-related data is scarce. With these AI-based technologies we extended the reliability of currently-available global nowcasts, on average, from zero to five days, and improved forecasts across regions in Africa and Asia to be similar to what are currently available in Europe. The evaluation of the models was conducted in collaboration with the European Center for Medium Range Weather Forecasting (ECMWF).

These technologies also enable Flood Hub to provide real-time river forecasts up to seven days in advance, covering river reaches across over 80 countries. This information can be used by people, communities, governments and international organizations to take anticipatory action to help protect vulnerable populations.

The ML models that power the FloodHub tool are the product of many years of research, conducted in collaboration with several partners, including academics, governments, international organizations, and NGOs.

In 2018, we launched a pilot early warning system in the Ganges-Brahmaputra river basin in India, with the hypothesis that ML could help address the challenging problem of reliable flood forecasting at scale. The pilot was further expanded the following year via the combination of an inundation model, real-time water level measurements, the creation of an elevation map and hydrologic modeling.

In collaboration with academics, and, in particular, with the JKU Institute for Machine Learning we explored ML-based hydrologic models, showing that LSTM-based models could produce more accurate simulations than traditional conceptual and physics-based hydrology models. This research led to flood forecasting improvements that enabled the expansion of our forecasting coverage to include all of India and Bangladesh. We also worked with researchers at Yale University to test technological interventions that increase the reach and impact of flood warnings.

Our hydrological models predict river floods by processing publicly available weather data like precipitation and physical watershed information. Such models must be calibrated to long data records from streamflow gauging stations in individual rivers. A low percentage of global river watersheds (basins) have streamflow gauges, which are expensive but necessary to supply relevant data, and its challenging for hydrological simulation and forecasting to provide predictions in basins that lack this infrastructure. Lower gross domestic product (GDP) is correlated with increased vulnerability to flood risks, and there is an inverse correlation between national GDP and the amount of publicly available data in a country. ML helps to address this problem by allowing a single model to be trained on all available river data and to be applied to ungauged basins where no data are available. In this way, models can be trained globally, and can make predictions for any river location.

Our academic collaborations led to ML research that developed methods to estimate uncertainty in river forecasts and showed how ML river forecast models synthesize information from multiple data sources. They demonstrated that these models can simulate extreme events reliably, even when those events are not part of the training data. In an effort to contribute to open science, in 2023 we open-sourced a community-driven dataset for large-sample hydrology in Nature Scientific Data.

Most hydrology models used by national and international agencies for flood forecasting and river modeling are state-space models, which depend only on daily inputs (e.g., precipitation, temperature, etc.) and the current state of the system (e.g., soil moisture, snowpack, etc.). LSTMs are a variant of state-space models and work by defining a neural network that represents a single time step, where input data (such as current weather conditions) are processed to produce updated state information and output values (streamflow) for that time step. LSTMs are applied sequentially to make time-series predictions, and in this sense, behave similarly to how scientists typically conceptualize hydrologic systems. Empirically, we have found that LSTMs perform well on the task of river forecasting.

Our river forecast model uses two LSTMs applied sequentially: (1) a hindcast LSTM ingests historical weather data (dynamic hindcast features) up to the present time (or rather, the issue time of a forecast), and (2) a forecast LSTM ingests states from the hindcast LSTM along with forecasted weather data (dynamic forecast features) to make future predictions. One year of historical weather data are input into the hindcast LSTM, and seven days of forecasted weather data are input into the forecast LSTM. Static features include geographical and geophysical characteristics of watersheds that are input into both the hindcast and forecast LSTMs and allow the model to learn different hydrological behaviors and responses in various types of watersheds.

Output from the forecast LSTM is fed into a head layer that uses mixture density networks to produce a probabilistic forecast (i.e., predicted parameters of a probability distribution over streamflow). Specifically, the model predicts the parameters of a mixture of heavy-tailed probability density functions, called asymmetric Laplacian distributions, at each forecast time step. The result is a mixture density function, called a Countable Mixture of Asymmetric Laplacians (CMAL) distribution, which represents a probabilistic prediction of the volumetric flow rate in a particular river at a particular time.

The model uses three types of publicly available data inputs, mostly from governmental sources:

Training data are daily streamflow values from the Global Runoff Data Center over the time period 1980 - 2023. A single streamflow forecast model is trained using data from 5,680 diverse watershed streamflow gauges (shown below) to improve accuracy.

We compared our river forecast model with GloFAS version 4, the current state-of-the-art global flood forecasting system. These experiments showed that ML can provide accurate warnings earlier and over larger and more impactful events.

The figure below shows the distribution of F1 scores when predicting different severity events at river locations around the world, with plus or minus 1 day accuracy. F1 scores are an average of precision and recall and event severity is measured by return period. For example, a 2-year return period event is a volume of streamflow that is expected to be exceeded on average once every two years. Our model achieves reliability scores at up to 4-day or 5-day lead times that are similar to or better, on average, than the reliability of GloFAS nowcasts (0-day lead time).

Additionally (not shown), our model achieves accuracies over larger and rarer extreme events, with precision and recall scores over 5-year return period events that are similar to or better than GloFAS accuracies over 1-year return period events. See the paper for more information.

The flood forecasting initiative is part of our Adaptation and Resilience efforts and reflects Google's commitmentto address climate change while helping global communities become more resilient. We believe that AI and ML will continue to play a critical role in helping advance science and research towards climate action.

We actively collaborate with several international aid organizations (e.g., the Centre for Humanitarian Data and the Red Cross) to provide actionable flood forecasts. Additionally, in an ongoing collaboration with the World Meteorological Organization (WMO) to support early warning systems for climate hazards, we are conducting a study to help understand how AI can help address real-world challenges faced by national flood forecasting agencies.

While the work presented here demonstrates a significant step forward in flood forecasting, future work is needed to further expand flood forecasting coverage to more locations globally and other types of flood-related events and disasters, including flash floods and urban floods. We are looking forward to continuing collaborations with our partners in the academic and expert communities, local governments and the industry to reach these goals.

Read more:

Using AI to expand global access to reliable flood forecasts - Google Research

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Generative AI for designing and validating easily synthesizable and structurally novel antibiotics - Nature.com

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Free AI tools offer enormous potential: they democratize access to generative AI, enabling users to harness the power of AI without investment. Remarkably, these free AI apps offer solutions from image creation to video production to writing assistance.

Also, given that a growing crowd of generative AI vendors is competing for marketshare, the practice of offering a free AI app at least on a trial basis is an important aspect of attracting users. So expect a still longer list of free AI software going forward.

Here are our picks for the top free AI tools for users and businesses in 2024:

Heres how the top eight free generative AI tools compare across key features typically expected in free AI tools, including the use for which they are best suited.

To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps 2024

ClickUp is an all-in-one project management tool that seamlessly integrates task management with artificial intelligence capabilities.

It offers a large suite of features like customizable dashboards, real-time chat for team collaboration, and visual widgets to track various project indicators like team members, tasks, sprints, and time tracking. Its AI tool, ClickUp Brain, delivers solutions across knowledge management, project management, and content creation.

Aside from its Free and Enterprise versions, ClickUp offers Unlimited and Business plans that start at $7 and $12 per user per month when billed monthly, respectively. ClickUp AI can be added to any paid plan for $5 per user per month.

A leading AI video tool, Synthesia AI is recognized for its ability to significantly reduce localization and voiceover expenses, cutting video production costs by up to 50%. This is a significant consideration for businesses or content creators looking to produce high-quality video content on a budget.

The platforms AI capabilities enable users to create videos from text scripts using natural language processing and computer vision. This in turn eases the video production process and makes it more accessible to a wider audience.

Synthesia AI offers three plans: Starter at $22 per month, Creator at $67 per monthboth billed annuallyand Enterprise, which offers custom pricing.

Notion AI extends the capabilities of the popular organization and productivity platform Notion by integrating AI to assist with content creation, summarization, and more. Notion AI can summarize content, generate ideas, draft rough copies, correct spelling and grammar, and even translate content, making it a versatile tool for a wide range of applications. Thus its a very handy tool for business meetings as well as personal brainstorming.

Notion offers Free, Plus, Business, and Enterprise plans. Plus and Business start at $8 and $15 per user per month when billed annually, respectively, and theres a Notion AI add-on starting at $8 per user per month.

ChatGPT, developed by OpenAI, is a huge leap forward in conversational AI as it gives users the ability to generate human-like text based on the prompts provided. This tools capabilities extend beyond simple text generation; it can understand context, answer questions, write essays, create content, and even code. The recent enhancements, allowing ChatGPT to see, hear, and speak, have further broadened its enormous scope as its not limited to textual inputs. By the way, also on the horizon: Sora, OpenAIs text-to-video tool.

Aside from its free plan, which grants access to GPT-3.5, it has a Plus tier at $20 per user per month, billed monthly, and a Team plan at $30 per user per month, billed monthly.

Grammarly goes beyond traditional spell-checking to offer a comprehensive AI writing assistant that enhances clarity, engagement, and correctness. Its AI-driven platform provides real-time suggestions to improve grammar, punctuation, style, and tone. Its a notable free AI tool for anyone looking to elevate their writing, be they professionals or students. Grammarlys ability to adapt to your writing style over time makes it a personalized AI tool for improving communication across various platforms and formats.

The premium versions of Grammarly deliver two plans: Business and Enterprise. The Business plan is dependent on team size but starts at $15 per user per month, while the Enterprise plan offers custom pricing.

Canva opens up design to anyone who uses the free AI tool with its user-friendly platform that guides users to create professional-quality graphics, presentations, and social media content. Its standout AI feature is Magic Studio, which groups all of Canvas AI tools in one place. Canva also has an extensive library of templates, images, and design elements, combined with intuitive drag-and-drop functionality, that makes it accessible to users with no prior design experience.

Canvas free version offers a wide range of features suitable for basic design needs, with Canva Pro and Canva for Teams at subscription fees of $6.49 per user per month and $12.99 per month for the first five people, respectively.

Zapier is a powerful tool that connects your favorite apps, such as Gmail, Slack, Mailchimp and more, to automate repetitive tasks without having to write code or rely on developers to build the integration. Its interface is simple to use and allows you to create automated workflows, known as Zaps, which can move information between your web apps automatically. With AI enhancements, Zapier can suggest the most useful Zaps for your needs and learn from your usage patterns to recommend optimizations.

Aside from Zapiers free plan, its tiered paid plans include Starter, Professional, and Team that start from $19.99, $49.99, and $69.99 per month when billed annually, respectively.

A leading AI image creation tool, Stable Diffusion is a state-of-the-art AI model thats capable of generating highly creative and customizable images from textual descriptions. This open-source AI tool democratizes access to powerful image generation capabilities, enabling artists, designers, and content creators to bring their visions to life. Stable Diffusions versatility is a real strength: its adaptable to various styles and themes, allowing users to create everything from fantastical landscapes to detailed character art.

As an open source tool, Stable Diffusion is available for free. Anyone interested can download and run the model on their own hardware or utilize various online platforms that host the model, some of which may offer additional features or services for a fee.

Free AI tools that are capable of creating content can supercharge how businesses and individuals produce written, audio, and video content. Tools like Stable Diffusion and ChatGPT excel in this area, offering users the ability to generate blog posts, scripts, and images using natural language processing. This feature is invaluable for marketers, content creators, and anyone looking to scale their content production without compromising quality.

Workflow automation features, as seen in tools like Zapier, streamline repetitive tasks by connecting different applications and automating actions between them. This capability is crucial for enhancing productivity, reducing manual errors, and freeing up time for more strategic work. Businesses can automate tasks such as data entry, email responses, and social media updates.

Design and media features in AI tools enable users to create professional-quality graphics, videos, and multimedia content without needing extensive design skills. These features remove the barriers to design entirely and allow small businesses, educators, and social media influencers to produce visually appealing content. Canva is a great example of a free AI design tool.

Code assistance features offered by tools like ChatGPT leverage AI to suggest code snippets, complete lines of code, and even debug code for developers. This enhances coding efficiency, reduces the likelihood of errors, and can significantly speed up the development process for software developers and engineers.

Conversational AI features enable AI tools to understand and respond to human language in a way that mimics natural conversation. This is used more and more in AI chatbots, virtual assistants, and interactive learning platforms, especially since some of these use cases have previously produced a rather robotic and unintuitive experience for users. These AI tools provide users with instant, intelligent responses to their queries and improve user engagement.

AI writing assistance features like those in Grammarly offer real-time suggestions for grammar, punctuation, style, and tone improvements and ultimately make written communication clearer and more effective. This feature is particularly beneficial for non-native English speakers, professionals looking to polish their writing, and anyone who wants to improve their written communication skills.

AI image generation features such as those offered by Stable Diffusion allow users to create detailed and creative images from text. This feature opens up new possibilities for artists, designers, and content creators as they can now so easily visualize concepts and ideas quickly and bring their creative visions to life.

For a full portrait of the AI vendors serving a wide array of business needs, read our in-depth guide:150+ Top AI Companies 2024

Selecting the right free AI tools for your business hinges on answering the question, What do I need? and understanding what AI tool and how the tool can provide value.

Your use case really matters. For instance, startups might prioritize tools like Canva for quick and professional-grade design, while a tech company might find ChatGPT invaluable for coding assistance. Its about matching the tools strengths with your business requirements. But most important, if its a free AI tool you seek, check if the AI tools you are considering are actually free as its common to find a tool claiming to offer free features behind a premium plan.

To select these eight tools, we first had to ensure that each tool in our shortlist was free to use or had a free plan. We then considered a collection of tools that showed diversity in their use cases, ranging from image generation to code assistance. Then, we tested each of these tools to understand what they offer and how effective their free features are.

From the hands-on experience, we were able to determine the standout quality, strengths, and weaknesses of each tool. Finally, we compared the pricing of tools with premium pricing tiers.

Free AI tools present an attractive opportunity for businesses to implement AI capabilities with no financial investment. By selecting tools that meet your business needs and understanding their limitations, you can seamlessly integrate AI into your operations, which in turn improves efficiency and innovation. Ultimately, examine the tools that interest you closely and make sure that they are actually free to use or have a free plan as opposed to merely a free trial.

For more information about generative AI providers, read our in-depth guide: Generative AI Companies: Top 20 Leaders

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Top 8 Free AI Tools in 2024 - eWeek