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https://palmacedar.com ICT | Digital Services | Web & Application | SEO Company in Nigeria Thu, 29 Dec 2022 17:42:14 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 https://palmacedar.com/wp-content/uploads/2020/04/cropped-Palmacedar_Limited-New-Logo-1-150x150.png Blog – Palmacedar Limited https://palmacedar.com 32 32 3 Essay Writing Pointers to Help You Create Your Own Episodic Intense Essay https://palmacedar.com/3-essay-writing-pointers-to-help-you-create-your-own-episodic-intense-essay/?utm_source=rss&utm_medium=rss&utm_campaign=3-essay-writing-pointers-to-help-you-create-your-own-episodic-intense-essay Thu, 29 Dec 2022 17:42:14 +0000 https://palmacedar.com/?page_id=13447

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– Hire professional editors. Academic writers are not cheap so you do not wish to cut corners when employing a professional editor for the urgent essay writing demands. There are different kinds of editors that you can employ based on the theme of your job. Some edit using traditional methods while others are going to edit using particular software applications. If you are interested in finding a less expensive means of editing your essays, you may always hire the services of a ghostwriter.

]]> Understanding of and by Deep Knowledge https://palmacedar.com/blog/understanding-of-and-by-deep-knowledge/?utm_source=rss&utm_medium=rss&utm_campaign=understanding-of-and-by-deep-knowledge Wed, 15 Jun 2022 09:16:30 +0000 https://palmacedar.com/?page_id=12186

Understanding of and by Deep Knowledge: How knowledge constructs can transform AI from surface correlation to comprehension of the world

What knowledge makes you intelligent? What are the constructs used by your cognition to understand the world, interpret new experiences, and make thoughtful choices? Defining a framework that articulates the kinds of knowledge that enable understanding and higher cognition for humans or artificial intelligence (AI) will facilitate a structured discussion on ways to effectively materialize these constructs and chart a path to more intelligent machines.

Knowledge constructs that allow an AI system to organize its view of the world, comprehend meaning, and demonstrate understanding of events and tasks will likely be at the center of higher levels of machine intelligence. Machine cognition will expand beyond data to be anchored in knowledge constructs including dimensions such as descriptive knowledge, models of the world dynamics, and provenance, among others.

When studying language, we distinguish between form and meaning: form refers to the symbols — the surface expressions — used to express meaning. Each form has a particular meaning in a particular context, and forms can have different meanings in different contexts. As summarized in an article by Schölkopf, Bengio et al, “the majority of current successes of machine learning boil down to large scale pattern recognition on suitably collected independent and identically distributed (i.i.d.) data.” Systems ingest observable elements such as text characters, vocal signals and image pixels, and establish patterns and stochastic correlations, while yielding outstanding results for recognition-based tasks.

There is growing agreement that algorithms must go beyond surface correlations into meaning and understanding to achieve a higher level of machine intelligence. This categorical shift will enable what is referred to as System 2, 3rdWave, or broad generalization/flexible AI. As I outlined in the core blog ‘The Rise of Cognitive AI’, this next level of machine intelligence requires deep constructs of knowledge that can transform AI from surface correlation to comprehension of the world, representing abstractions, relations, learned experiences, insights, models and other types of structured information.

John Launchbury of DARPA calls out the aspects of AI that will see a transformational improvement in the 3rd wave of AI as abstraction (i.e., creating new meaning) and reasoning (planning and deciding). The 3rd wave itself is characterized by contextual adaptation where systems construct contextual explanatory models for classes of real-world phenomena. The framework presented here offers a perspective on how knowledge constructs will facilitate such a leap.

Two of the knowledge dimensions reflect a view of the world — the descriptive dimension with its conceptual abstractions of what is in the world, and the dynamic models of the real world and its phenomena. Stories add the human capacity to comprehend and communicate complex narratives that build on shared beliefs and mythologies. Context and source attribution as well as value and priorities are meta-knowledge dimensions that provide a condition-based overlay of validity and knowledge-about-knowledge. Finally, concept references are the structural underpinning, binding across dimensions, modalities and references. Together, these six dimensions of knowledge could bring additional depth beyond correlation of events by assuming underlying concepts that are persistent and can explain and predict past and future events, allow for planning and intervention, and consider counterfactual realities — hence the use of the term ‘deep knowledge.’

Articulating and characterizing the kinds of knowledge constructs necessary for machine intelligence can contribute to identifying the best way to implement them to bring about the next level of machine intelligence. The goal of this blog is to establish the fundamental classes of knowledge constructs deemed relevant for the development of the next level of AI cognitive capabilities.

Dimensions of Knowledge in Support of Higher Intelligence

For AI systems, implementing knowledge constructs observed in human comprehension and communication can provide substantial value to intelligence. That value grows substantially when all knowledge types are supported and combined.

1. Descriptive knowledge: Hierarchy, taxonomies and property inheritance

Descriptive knowledge, (i.e., conceptual, propositional or declarative knowledge) describes things, events, their attributes and their relationships to each other. The notion of deep descriptive knowledge expands on this definition, assuming the use (as appropriate) of hierarchical layering of classes or concepts. This category of knowledge can include facts and systems of records. The facts and information relevant for specific use cases and environments can be organized, utilized and updated as hierarchical knowledge.

The underlying ontology used in individual AI systems can be seeded with task-relevant classes and entities from curated systems (e.g., the OpenCyc ontology or the AMR named entity types). It should be extensible with neural network/machine learning technologies — the acquisition of new knowledge will contribute new entities, relations and classes.

2. Models of the world

Models of phenomena in the world enable AI systems to understand situations, interpret inputs/events, predict potential future outcomes and take action. These models are abstractions/generalizations and can be divided into formal models and approximate (informal) real-world models; they allow for the use of variables and the application to instances in particular cases, and enable symbol manipulation of a particular instance or a more generalized class.

Examples of formal models include logic, mathematics/algebra and physics. In contrast to formal models, real-world models are usually empirical, experimental and sometimes messy. They include both physical as well as psychological and sociological models. Procedural models (‘know-how’) are included in this class.

Causality models are a prime example of the types of models that can help progress AI systems to the next level of machine intelligence. In cases of changed context, statistics of the past can only be effectively applied to the present to predict futures, if integrated with a knowledge model such as causality and with the understanding of the context that governs the causes in play and the ability to consider counterfactuals. These models help in understanding situations or events in terms of the conditions and likely factor…. Causal reasoning is an indispensable component of human thought that can be formalized toward achieving human-level machine intelligence.

3. Stories and Scripts

Stories form a key part of the culture and world view of individuals and societies — as was stated by the historian Yuval Harari. The notion of stories is necessary to fully understand and interpret human behavior and communication. Stories are complex and may include multiple events and a variety of information within a connective narrative. They are not just collections of facts and events. Instead, they contain crucial information that helps develop understanding and generalizations beyond the presented data. Unlike models of the world which are expected to provide an operational representation of the world and how one can interact with it, stories can be viewed as historical, referential or spiritual. Stories can represent values and experiences that inform people’s beliefs and actions. Examples include religious or national stories, mythology, and shared stories at any level of groups of people.

4. Context and source attribution

Context can be defined as a frame that surrounds an event or other information and provides resources for its appropriate inte…. It can be seen as an overlaid knowledge structure, modulating the knowledge it encloses. Context can be persistent or transient.

· Persistent context can be long lasting (as in knowledge that is captured from a western vs. eastern philosophy perspective) or it can change over time based on material new learning. It does not change per task.

· Transient context is relevant where particular local context is important. Words are interpreted in the local context of their surrounding sentence or paragraph. Regions of interest in an image are commonly interpreted in context of the overall image or video.

The combination of the persistent and transient context can provide the complete setting to interpret and operationalize knowledge.

Another related aspect of knowledge is data provenance (aka data lineage), which includes data origin, what happens to it and where it moves over time. An AI system cannot assume that all information ingested is generally correct or trustworthy, especially in regard to what has been dubbed as post-truth era. Associating information with its sources might be necessary for establishing credibility, certifiability and traceability

5. Value and Priorities (including goodness/threats and ethics)

All aspects of knowledge (e.g., object, concept, or procedure) can have an associated value across the judgment spectrum — from utmost goodness to greatest evil. It can be assumed that evolution of human intelligence includes the pursuit of rewards and avoiding risks (get lunch; avoid being lunch). This risk/reward association is tightly coupled with the knowledge of things. The potential of gain vs. loss has a utilitarian value; there is also an ethics-based value for entities or potential future states being considered. This can reflect the ethical values that assign “goodness” based not on potential tangible rewards or threats, but rather on an underlying belief of what is right.

Value and priorities are meta-knowledge that reflect the subjective assertion of the AI system about relevant aspects of knowledge, actions and outcome. It establishes the foundation for accountability and should be carefully addressed by those responsible for the particular AI system. When AI systems interact with humans and make choices that affect the humans’ well-being, the underlying value and prioritization system matters.

6. Concept References: disambiguated, unified and cross-modal

Knowledge is based on concepts. For example, “dog” is an abstraction — a concept that has multiple names (e.g., in various languages), some visual characteristics, sound association and so on. However, the underlying concept /dog/ is unique, regardless of its manifestations and usages. It is mapped to the English word “dog,” as well as mapped to the French word “chien.” It is also a property belonging to and the likely source of a barking sound.

A Concept Reference (or ConceptRef for short) is the identifier and set of references to all things related to a given concept. The ConceptRefs by themselves don’t actually include any of the knowledge — the knowledge resides in the dimensions described above. ConceptRefs are the linchpins of a multi-dimensional knowledge base (KB); as they amalgamate all appearances of the concept.

Wikidata is an excellent example of a KB that centrally stores structured data. In Wikidata, items represent all the things in human knowledge, including topics, concepts, and objects. Wikidata’s items are similar to the definition of ConceptRef in this framework — with one key difference. In Wikidata, the term “items” refers to both the given identifier, along with the information about it. ConceptRefs are just the identifiers with the pointers to the KB. The information about the concept is populated in the various views described in previous sections (such as descriptive or procedural knowledge associated with a concept).

Commonsense knowledge

Commonsense knowledge consists of implicit information — the broad (and broadly shared) set of unwritten assumptions that humans automatically apply to make sense of the world. Applying commonsense to situations is essential for understanding and higher cognition. In this framework, commonsense knowledge is considered a subset of each of the above six knowledge types.

The Relationship Between Understanding and Knowledge Types

Understanding is the foundation of intelligence. The impending transition to higher machine intelligence has ignited a discussion on ‘understanding’. Yoshua Bengio characterized human-level AI understanding as follows: capture causality and how the world works; understand abstract actions and how to use them to control, reason and plan, even in novel scenarios; explain what happened (inference, credit assignment); and out-of-distribution generation.

Consider the following knowledge-centric definition of understanding: the ability to create a world view expressed with rich knowledge representation; the ability to acquire and interpret new information to enhance this world view; and the ability to effectively reason, decide and explain over existing knowledge and new information.

Four functions are a prerequisite for this view of understanding: representing rich knowledge, acquiring new knowledge, linking the instances of knowledge across entities and relations, and reasoning over knowledge. Naturally, understanding is not a binary property but instead varies by type and degree. At the center of this view is the nature of knowledge and its representation — the expressivity of knowledge constructs and models can facilitate a categorical difference in the ability to understand and reason.

Imagine all the people [and machines]

As Albert Einstein observed, “The true sign of intelligence is not knowledge but imagination.” To truly understand, machine intelligence must go beyond knowledge of data, facts and stories. Imagination is necessary to reconstruct, discover and invent a model of the universe behind the observable attributes and events. From an AI system’s perspective, imagination is achieved through creative reasoning: performing inductive, deductive or abductive reasoning and generating novel outcomes not strictly prescribed by previous experiences and input-to-output correlations.

Knowledge representation and reasoning is a well-established field of AI that addresses representation of information about the world so a computer system can solve complex tasks. Knowledge and reasoning are not necessarily distinct, but rather represent a spectrum from the known to the inferred (which can become a new known). Machine understanding will be achieved through the capacity to construct knowledge, complemented by advanced and updated associated reasoning (e.g., probabilistic and plausible reasoning, abductive reasoning, analogical reasoning, default reasoning, etc.).

Neuro-symbolic AI Built on Deep Knowledge Foundations

My appreciation for a more cognitive, knowledge-based approach to AI emerged in the mid 2010s while working on deep learning hardware and software solutions at Intel. Gary Marcus’ excellent paper The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence offers a similar perspective.

In the journey to make AI more effective, accountable, and productive in support of people, the goal is to make AI systems more robust, while also driving them to the next level of cognition and comprehension. Great strides have been made in manipulating data, recognizing patterns, and finding the most fleeting of correlations. But it’s still necessary to consider the types of knowledge that will equip an AI system with the capabilities to model and understand the world it operates in.

The time has come for a dialogue on the kinds of knowledge that are required for a more cognitive AI. The types of constructs for knowledge representation discussed in this blog may be implementable in various forms, and the resulting systems will vary in the way neural network capabilities and symbolic knowledge (in whatever representation) achieve the goals of the next phase of AI. Subsequent blogs will address the different dimensions of knowledge introduced in this framework in more detail. As we establish a deeper understanding of the types of knowledge constructs needed for higher cognition, we can proceed to build on this deep knowledge to enable machine comprehension of the world.

References

Fillmore, Charles. “Form and Meaning in Language”. CSLI Publications, 2002. https://web.stanford.edu/group/cslipublications/cslipublications/site/1575862867.shtml (accessed on 05/04/2021)

Schölkopf, B. et al., “Towards Causal Representation Learning”. https://arxiv.org/abs/2102.11107

Bengio. Yoshua. “From System 1 Deep Learning to System 2 Deep Learning”.NIPS 2019, https://slideslive.com/38922304/from-system-1-deep-learning-to-system-2-deep-learning

Launchbury, John. “A DARPA Perspective on Artificial Intelligence”. DARPA, https://www.darpa.mil/attachments/AIFull.pdf (accessed on 23 March 2021)

Chollet, Francois. “What is the Future of Artificial Intelligence?”, https://www.youtube.com/watch?v=GpWLZUbPhr0

Singer, Gadi. “The Rise of Cognitive AI”. Toward Data Science, April 2021. https://towardsdatascience.com/the-rise-of-cognitive-ai-a29d2b724ccc

Forbus, Kenneth. “A Brief Introduction to the OpenCyc Ontology”. https://www.qrg.northwestern.edu/nextkb/IntroOpenCycOnt.pdf (accessed on 05/04/2021)

Newell, Allen. “Physical Symbol Systems”, Cognitive Science, April 1980. https://onlinelibrary.wiley.com/doi/abs/10.1207/s15516709cog0402_2

Pearl, Judea. “The Book of Why”. New York, Basic Books, May 2018. http://bayes.cs.ucla.edu/WHY/

Harari, Yuval Noah. “Sapiens, A Brief History of Humankind”. Harvill Secker, 2014.

De Jong, Tom and Fergusson-Hessler, Monica. “Types and Qualities of Knowledge”. Educational Psychology, 1996.

Pavlus, John. “Common Sense comes closer to Computers”. Quantamagazine, April 2020. https://www.quantamagazine.org/common-sense-comes-to-computers-20200430/

Marcus, Gary. “The Next Decade in AI: Four Steps Toward Robust Artificial Intelligence”. Robust AI, February 2020, https://arxiv.org/ftp/arxiv/papers/2002/2002.06177.pdf

]]> How to Bring Hybrid Core into Web https://palmacedar.com/blog/how-to-bring-hybrid-core-into-web/?utm_source=rss&utm_medium=rss&utm_campaign=how-to-bring-hybrid-core-into-web Thu, 09 Jun 2022 12:19:09 +0000 https://palmacedar.com/?page_id=12181

According to the usage statistics of user application from Microsoft, 60% of the time people spend on the PC is within the web browser. Google Chrome is a cross-platform web browser developed by Google based on Chromium project. According to StatCounter website stats, by January 2022, the market share of Chrome browser is over 63% across all platforms worldwide.

Hybrid core architecture combining high performance cores and power-efficient cores became more and more popular, especially after Intel launched the Alder Lake CPU product. Performance cores are designed to provide maximum compute performance, while efficient cores are designed for maximum power efficiency. Usually OS schedulers can manage hybrid core scheduling, but they lack details of application behaviors, like critical paths. It’s difficult for OS schedulers to cover all scenarios.

We come from the Web Optimization team, and focus on power and performance optimization for Web platforms, mainly Chromium, aiming for better user experience on IA. This article introduces our work to utilize hybrid core capability to schedule specific threads/processes’ execution in Chrome browser to efficient cores, which adopts dynamic policies to reduce power consumption on different levels based on device state. All the analysis and tests below are performed on the Chrome OS platform.

Overview

On the hybrid core platform, Chrome can schedule threads to efficient cores to save power consumption. However, putting browser threads on efficient cores all the time is impractical since lots of threads may surge and demand higher performance. So we propose a hybrid core scheduling technology in Chrome browser to apply dynamic throttles on specific non-critical threads through scheduling them to efficient cores to execute. The technology is based on Web runtime scenarios, like background/idle/ads/video, as the importance of threads would change in different scenarios. Moreover, device information, like battery/thermal status and hybrid core information, need to be exposed to Chrome. Based on them, hybrid core scheduling would apply different core allocation policies to balance power and performance. Normally we schedule low priority threads to efficient cores. But when the device is in a critical stage like running out of battery, the scheduling policy would be more aggressive to prolong device usage time. The application of scheduling policy relies on the OS support, and we can use thread priority or QoS mechanism according to the customs of the OS. On Chrome OS, currently we change thread priority and its cgroup association. Whole architecture of the proposal is shown in Figure 1.

Figure 1: hybrid core scheduling in Chrome browser

Implementation

The implementation of hybrid core scheduling technology mainly contains three parts, scenario detection, scheduling policy, and OS support work.

Scenario detection

First we need to determine the current scenario of a process based on inputs from various browser components. For example, the Chrome render process has a status about background state, which indicates whether the process is foreground or background scenario. For another example, Chrome has an Ad Tagging mechanism to detect ads and the resources they load in the browser. Ad Tagging works by matching resource requests against a filter list to determine if they’re ad requests. An iframe will be marked as an ad iframe if its url matches the filter list, if the tagged script is involved in the creation of the iframe, or if its parent frame is an ad iframe. If all frames are ad frames, the render process would be tagged as an ad process. The browser collects all these inputs and uses a prioritization mechanism to decide the overall mode for the process. Based on the scenario, we adopt an appropriate scheduling policy next.

Scheduling policy

The scheduling policy varies based on the device status. As shown in Figure 1, the browser will monitor the power status of the device via APIs provided by the OS, including the battery level, charging status and the thermal state. For hybrid core scheduling, two stages are defined below.

The first one is the normal stage, which means the battery level is over 20% or the device is charging, meanwhile the thermal state is normal. In this stage, the users care more about the performance than power consumption, so we only schedule low priority threads/processes to efficient cores, like the background processes or the threads handling low priority tasks such as logging/profiling.

The second one is the critical stage, which means the battery level is very low without charging, or the device is in critical thermal states, or the web developer explicitly wants to enter power saving mode, like using battery-savings meta tag. In this stage, we’re going to apply more aggressive policies to save more power, prolong device usage time or avoid thermal throttling due to high CPU temperature. Under this circumstance, many threads/processes in normal priority will be scheduled to efficient cores as long as they are not involved in UX critical tasks.

OS support work

There is some work required to be done to make Chrome utilize OS capability. Battery and thermal status are two important factors to UX. Based on them, Chrome could make appropriate policies to balance performance and power consumption. Previously, there was only battery status exposed to Chrome. Our team has landed a thermal status notification feature in Chrome. In the feature, we introduced 4 thermal levels: Nominal, Fair, Serious, and Critical referring to Apple’s Thermal Hinting API. So that Chrome can get the real-time thermal status. With battery level, charging and thermal status reported, Chrome would decide which stage to enter and apply different scheduling policies.

Furthermore, we have built a bridge between Chrome threads and efficient cores on Chrome OS using the existing cgroup mechanism. Background priority threads are placed in a specific cgroup, which has a specified CPU set. On hybrid core platforms, efficient cores are likely to be allocated for the group. So if we want to schedule unimportant threads to efficient cores to execute, we can lower the thread priority and put them in the non-urgent cgroup. The scheduling is dynamic. When the threads become important (e.g. switch to foreground), we would raise the thread priority to normal right away, hence remove from the specific cgroup.

Experiments

We use the local build Chromium browser to evaluate the power impact of hybrid core scheduling per each scenario, currently focusing on background renderer processes, ads processes, and idle processes (idle is a state defined in the Chrome RAIL model). According to the experiments performed on Alder Lake Chromebook, we observe 4.2% CPU package power reduction for web browsing when scheduling idle processes to efficient cores, and 3.8% CPU package power reduction when dispatching advertisement processes. At the same time, we use a 4-tab browsing workload to test the power impact of placing background processes on efficient cores, and see 0.9% CPU package power reduction. The power saving would be larger when the number of background tabs and page activities increase.

The experiment data shows that we achieve distinct power reduction by utilizing hybrid core capability in Chromium browser to schedule non-UX critical processes/threads to efficient cores in chosen scenarios, which helps extend device battery life.

Future Work

We will continue to explore more scenarios, which don’t demand high performance, and corresponding processes/threads can be scheduled to efficient cores. Besides, as for some scenarios like ads and idle, running on efficient cores might have performance impact, we are about to conduct performance evaluation soon and adjust the scheduling policy accordingly. Furthermore, we intend to extend our analysis and hybrid core scheduling optimization to Windows and Linux platforms.

]]> What Is a Hotspot? – WiFi Hotspot Definitions and Details https://palmacedar.com/what-is-a-hotspot-wifi-hotspot-definitions-and-details/?utm_source=rss&utm_medium=rss&utm_campaign=what-is-a-hotspot-wifi-hotspot-definitions-and-details Fri, 03 Jun 2022 11:04:20 +0000 https://palmacedar.com/?page_id=12170

Hotspots—what are they, where are they, and how can you connect to them while protecting your privacy and security?

If you’ve ever tried to answer an email or surf the Internet from your mobile device in public—or even at the office or your house—chances are you connected to a Wi-Fi hotspot. Not only is this connection highly convenient, you also didn’t have to use your smartphone’s data. Not surprisingly, hotspots are becoming an essential part of public infrastructure—and our Internet experience.

Millions of people every day connect to public hotspots for their data needs. By some estimates, there are almost 200 million hotspots around the world, and there will be one hotspot for every 20 people on earth by 2018. Thanks to our modern always-on digital lifestyle, people expect to be constantly connected, and public Wi-Fi access points are expanding to a global network of hotspots to meet those needs.

Before we dive in to how to connect to a hotspot and related security issues, let’s define what we mean. While some people use the terms “hotspot” and “mobile hotspot” interchangeably, they have distinct meanings.

Hotspot: A hotspot is a physical location where people can access the Internet, typically using Wi-Fi, via a wireless local area network (WLAN) with a router connected to an Internet service provider. Most people refer to these locations as “Wi-Fi hotspots” or “Wi-Fi connections.” Simply put, hotspots are the physical places where users can wirelessly connect their mobile devices, such as smartphones and tablets, to the Internet.
A hotspot can be in a private location or a public one, such as in a coffee shop, a hotel, an airport, or even an airplane. While many public hotspots offer free wireless access on an open network, others require payment. Later in the article you’ll learn how to connect a mobile device to a Wi-Fi hotspot.
Mobile hotspot: A mobile hotspot (sometimes called a portable hotspot) is a hotspot that’s just that—mobile! While a “regular” Wi-Fi hotspot is tied to a physical location, you can create a mobile hotspot by using your smartphone’s data connection to connect your laptop to the Internet. This process is called “tethering.” More on this process later.
You should also know these terms when you’re talking about Wi-Fi hotspots.
Access point (wireless access point): A wireless access point (WAP) is a networking device that allows a Wi-Fi compliant device to connect to a wired network. The WAP can either be physically connected to a router or be integrated into the router itself. A WAP is not a hotspot, which is the physical location where Wi-Fi access to a WLAN is available.
Wi-Fi: Wi-Fi is the technology that allows your smartphone or computer to access the Internet through a wireless connection. It uses radio signals to send and receive data between your enabled device and the WAP.
SSID: A service set identifier (more commonly known as an SSID) is the unique name of a wireless network. You’ll need to know the name of the wireless network to connect to it. Your computer or smartphone can search for available wireless networks; often people name their network for easy identification—anything from “Bob’s phone” to “hotel guests” to “Get off my LAN.”

Now that you understand some of the terms associated with hotspots, let’s learn how to connect to them.

How to Connect to a Wi-Fi Hotspot

You probably connect your smartphone or laptop to the Internet via several Wi-Fi hotspots throughout your day, whether you’re at your office, in your home, or at public locations like coffee shops and airports. Using hotspots is an easy way to keep connected to your busy life.

Connecting to a wireless hotspot is a simple process. Let’s use your smartphone as an example. You want to answer an email at the airport while you’re waiting for your flight, and you don’t want to use your data. You can set your smartphone to notify you when it’s in range of a wireless network, or you can find wireless networks through your phone’s settings. The steps you need to follow to connect to the Wi-Fi hotspot will depend on the device—Android*, iPhone*, or another brand—but here is an overview.

Click the wireless icon on your device to see the names of nearby wireless networks. Select a wireless network; in some cases, you might also have to click “Connect.”
Enter the security key or the password. Most wireless networks are secured and require a password to accept a connection. Some networks are unsecured or open and do not require a password; you should take care when accessing them as they could introduce a security risk.
Select the network type (home, work, or public, if you are on a Windows* device). Choosing the network type will establish a security level appropriate for your location. If you select “home” or “work,” your device will be discoverable to other devices. Be sure to select “public” if you are in a public location like a coffee shop, hotel, restaurant, airport, and other similar locations.

Depending on where you are and the types of hotspots near you, you may be on either an open, unsecured wireless network or a paid/commercial wireless network. You may be asked to sign up for an account or use a paid service like Boingo* or iPass*, which offer various Wi-Fi access plans depending on how much time you plan use the Internet.

Let’s say, though, that you can’t find a Wi-Fi hotspot nearby. Read on to learn how you can use your smartphone as a portable hotspot.

Using Your Smartphone as a Mobile Hotspot

If you’re in a location that doesn’t have a hotspot and you want to connect your laptop to the Internet, you can use your phone as a mobile Wi-Fi hotspot through a process called “tethering.” This allows your laptop to access the Internet and share your smartphone’s data connection.

While the set-up steps vary depending on your smartphone and your Internet service provider, you can usually find the instructions in your phone’s Settings or Manage Connections menu. For security, you’ll want to make sure that you use a Wi-Fi password so that nearby Internet users can’t access your phone or laptop. Also, be aware that tethering your laptop to your phone will use your phone’s data allowance; so be sure to keep an eye on your usage to avoid any overage fees.

Now that you’re connected, that’s it, right? Well, not exactly. You should be aware that while using Wi-Fi hotspots is a convenient way to stay connected with work, family, and friends. Hotspot connectivity also presents some security risks.

Hotspot Security

One of the risks of being connected to the Internet is that the very technologies that help us keep up with our work and personal lives can be vulnerable to hackers and identity thieves.

When looking for a public Wi-Fi hotspot, be sure to connect your smartphone or laptop only to reputable providers—for example, the hotel’s or coffee shop’s wireless network. Be wary about connecting to hotspots that have misspellings such as Bongo instead of Boingo, as hackers sometimes use these seemingly innocent names to lure busy users who aren’t paying close attention.

It’s also possible for hackers to distribute malware (software that can damage or disable your computer) through an unsecured Wi-Fi connection, especially if you are using a file-sharing program over the same network.

Virtual Private Network (VPN)

If you have security concerns about using a public Wi-Fi hotspot, you could consider creating a virtual private network (VPN), which allows you to use to the Internet through an encrypted connection. While this can deter hackers because your data is encrypted, be aware that it will slow down your Internet access because of the processing power required to encrypt and decrypt your transmitted data.

Find a VPN Solution that Works

If you’re interested in using a VPN to safeguard yourself online:

Invest in a monthly service. This is one of the most commonly used solutions. Make sure to do your research before you buy.
Consider purchasing a VPN-enabled router. There are several models on the market that make setting up your own VPN easy.

With more than 9 billion Wi-Fi-enabled mobile devices expected to be in use by the end of the year, the importance of hotspots and Wi-Fi in our lives really can’t be overstated.

Signals Straight

	A.K.A	Purpose
WLAN	Wireless local area network Wireless LAN	Allows mobile devices to communicate without wires using radio or infrared signals
WiMAX	Worldwide Interoperability for Microwave Access	Once thought to be the successor to Wi-Fi, offered wireless broadband access before succumbing to competing wireless standards
5G	5th generation of the mobile wireless standard	Will offer greater data rates, faster Internet connection and download speeds (when launched in 2020)

A.K.A

Purpose

WLAN

Wireless local area network

Wireless LAN

Allows mobile devices to communicate without wires using radio or infrared signals

WiMAX

Worldwide Interoperability for Microwave Access

Once thought to be the successor to Wi-Fi, offered wireless broadband access before succumbing to competing wireless standards

5th generation of the mobile wireless standard

Will offer greater data rates, faster Internet connection and download speeds (when launched in 2020)

]]> WHAT TYPES OF BIOLOGICAL AND HEALTH EFFECTS CAN BE EXPECTED FROM 5G WIRELESS NETWORKING TECHNOLOGY? https://palmacedar.com/blog/what-health-effects-can-be-expected-from-5g-wireless-networking/?utm_source=rss&utm_medium=rss&utm_campaign=what-health-effects-can-be-expected-from-5g-wireless-networking Thu, 02 Jun 2022 11:10:50 +0000 https://palmacedar.com/?page_id=12165 Wireless communications have been expanding globally at an exponential rate. The latest imbedded version of mobile networking technology is called 4G (fourth generation), and
the next version (called 5G – fifth generation) is in the early implementation stage. Neither 4G nor 5G have been tested for safety in credible real-life scenarios. Alarmingly, many of the
studies conducted in more benign environments show harmful effects from this radiation. The present article overviews the medical and biological studies that have been performed to date
relative to effects from wireless radiation, and shows why these studies are deficient relative to safety. However, even in the absence of the missing real-life components such as toxic
chemicals and biotoxins (which tend to exacerbate the adverse effects of the wireless radiation), the literature shows there is much valid reason for concern about potential adverse
health effects from both 4G and 5G technology. The studies on wireless radiation health effects reported in the literature should be viewed as extremely conservative, substantially underestimating the adverse impacts of this new technology.

The potential 5G adverse effects derive from the intrinsic nature of the radiation, and its interaction with tissue and target structures. 4G networking technology was associated mainly with carrier frequencies in the range of ~1-2.5 GHz (cell phones, WiFi). The wavelength of 1 GHz radiation is 30 cm, and the penetration depth in human tissue is a few centimeters. In its highest performance (high-band) mode, 5G networking technology is mainly associated with carrier frequencies at least an order of magnitude greater than the 4G frequencies, although, as stated previously, “ELFs (0–3000Hz) are always present in all telecommunication EMFs in the form of pulsing and modulation”.

Penetration depths for the carrier frequency component of high-band 5G wireless radiation will be on the order of a few millimeters. At these wavelengths, one can expect resonance phenomena with small-scale human structures. Additionally, numerical simulations of millimeter-wave radiation resonances with insects showed a general increase in absorbed RF power at and above 6 GHz, in comparison to the absorbed RF power below 6 GHz. A shift of 10% of the incident power density to frequencies above 6 GHz was predicted to lead to an increase in absorbed power between 3–370%.

The common ‘wisdom’ presented in the literature and media is that, if there are adverse impacts resulting from high-band 5G, the main impacts will be focused on near-surface phenomena, such as skin cancer, cataracts, and other skin conditions. However, there is evidence that biological responses to millimeter-wave irradiation can be initiated within the skin, and the subsequent systemic signaling in the skin can result in physiological effects on the nervous system, heart, and immune system.

Additionally, consider the following reference [Zalyubovskaya, 1977]. This is one of many translations of articles produced in the Former Soviet Union on wireless radiation (also, see
reviews of Soviet research on this topic by McRee [1979, 1980], Kositsky [2001], and Glaser and Dodge [1976]). On p. 57 of the pdf link, the article by Zalyubovskaya addresses biological effects of millimeter radiowaves. Zalyubovskaya ran experiments using power fluxes of 10,000,000 microwatts/square meter (the FCC (Federal Communications Commission) guideline limit for the general public today in the USA), and frequencies on the order of 60 GHz.

Not only was skin impacted adversely, but also heart, liver, kidney, spleen tissue as well, and blood and bone marrow properties. These results reinforce the conclusion of Russel (quoted above) that systemic results may occur from millimeter-wave radiation. To re-emphasize, for Zalyubovskaya’s experiments, the incoming signal was unmodulated carrier frequency only, and the experiment was single stressor only. Thus, the expected real-world results (when human beings are impacted, the signals are pulsed and modulated, and there is exposure to many toxic stimuli) would be far more serious and would be initiated at lower (perhaps much lower) wireless radiation power fluxes.

The Zalyubovskaya paper was published in 1977. The referenced version was classified in 1977 by USA authorities and declassified in 2012. What national security concerns caused it (and the other papers in the linked pdf reference) to be classified for 35 years, until declassification in 2012? Other papers on this topic with similar findings were published in the USSR (and the USA) at that time, or even earlier, but many never saw the light of day, both in the USSR and the USA. It appears that the potentially damaging effects of millimeter-wave radiation on the skin (and other major systems in the body) have been recognized for well over forty years, yet today’s discourse only revolves around the possibility of modest potential effects on the skin and perhaps cataracts from millimeter-wave wireless radiation.

]]> Cloud security firm Lacework lays off 20% of staff https://palmacedar.com/cloud-security-firm-lacework-lays-off-20-of-staff/?utm_source=rss&utm_medium=rss&utm_campaign=cloud-security-firm-lacework-lays-off-20-of-staff Mon, 30 May 2022 11:58:01 +0000 https://palmacedar.com/?page_id=12159

The company did not specify how many employees in total were affected. Lacework had reported having more than 1,000 employees in March, following a $1.3 billion funding round at an $8.3 billion valuation in November.

A well-funded startup in the cybersecurity industry, Lacework, has become the latest tech firm to disclose a major round of layoffs amid fears of a broader economic slowdown.

In a statement provided to Protocol, Lacework confirmed that the layoffs impacted 20% of its employees, in connection with what it called a “decision to restructure our business.”

The company did not disclose how many employees in total have been laid off. Lacework had previously disclosed having more than 1,000 employees as of March 2022.

A Lacework representative said that a figure for the total number of employees affected by the layoffs shared on Twitter on Wednesday was a “significant overestimate.”

In a blog post Wednesday, the cloud security vendor said that “today, we made the very difficult decision to say goodbye to some of our colleagues, as part of a restructuring and modification to the company plan.”

The company has “taken every effort to provide those impacted with severance encompassing compensation, healthcare coverage, and access to outplacement support. As they pursue opportunities outside of the company we will help in whatever way we can,” the company said in its blog post, signed by co-CEOs David Hatfield and Jay Parikh.

Lacework has raised $1.85 billion in funding since its launch in 2014, most of which was announced in 2021. The company disclosed raising $525 million in January 2021, followed by a $1.3 billion funding in November 2021 that brought with it an eye-popping valuation of $8.3 billion. Lacework touted the fundraise as “the largest funding round in security industry history,” and the firm ranks at No. 3 in terms of the biggest valuations for privately held security companies, according to CB Insights.

The company has said that its customer base grew by 3.5X in 2021. Between the massive funding and rapid expansion of its business, Lacework went on a hiring spree last year — going from 200 employees in January 2021 to more than 1,000 as of March.

However, “over the past several weeks and months, a seismic shift has occurred in both the public and private markets,” the co-CEOs said in the post. “While we do not have control of the environment around us, we do have a responsibility to control how we operate our business and make changes as needed to best position the company for continued and long-term success.”

Lacework offers a “data-driven” service that aims to stand out in the fast-growing cloud security market by collecting and analyzing data from across a customer’s cloud environments. The goal is to to provide customers with crucial security insights, such as which threats should be prioritized for action, the company has said.

The Lacework platform supports AWS, Google Cloud, Microsoft Azure and Kubernetes (Amazon EKS) environments. Previously disclosed customers include VMware, Snowflake and Pure Storage.

Lacework is also notable for having been just the third company to be incubated out of Sutter Hill Ventures, following a model that was used to launch Pure Storage and Snowflake. The company is led by Hatfield, who was formerly the president of Pure Storage, and Parikh, previously Facebook’s vice president of engineering.

“Despite the broader economic environment – demand for cloud security will remain strong, and it is critical to all online, cloud businesses,” the co-CEOs said the post Wednesday.

]]> Superfast; NASA Spacecraft Touches the Sun for First Time Ever https://palmacedar.com/blog/superfast-nasa-spacecraft-touches-the-sun-for-first-time-ever/?utm_source=rss&utm_medium=rss&utm_campaign=superfast-nasa-spacecraft-touches-the-sun-for-first-time-ever Fri, 17 Dec 2021 10:57:46 +0000 https://palmacedar.com/?page_id=12063

For the first time in history, a spacecraft has touched the Sun. NASA’s Parker Solar Probe has now flown through the Sun’s upper atmosphere – the corona – and sampled particles and magnetic fields there.

The new milestone marks one major step for Parker Solar Probe and one giant leap for solar science. Just as landing on the Moon allowed scientists to understand how it was formed, touching the very stuff the Sun is made of will help scientists uncover critical information about our closest star and its influence on the solar system.

“Parker Solar Probe “touching the Sun” is a monumental moment for solar science and a truly remarkable feat,” said Thomas Zurbuchen, the associate administrator for the Science Mission Directorate at NASA Headquarters in Washington. “Not only does this milestone provide us with deeper insights into our Sun’s evolution and its impacts on our solar system, but everything we learn about our own star also teaches us more about stars in the rest of the universe.”

As it circles closer to the solar surface, Parker is making new discoveries that other spacecraft were too far away to see, including from within the solar wind – the flow of particles from the Sun that can influence us at Earth. In 2019, Parker discovered that magnetic zig-zag structures in the solar wind, called switchbacks, are plentiful close to the Sun. But how and where they form remained a mystery. Halving the distance to the Sun since then, Parker Solar Probe has now passed close enough to identify one place where they originate: the solar surface.

The first passage through the corona – and the promise of more flybys to come – will continue to provide data on phenomena that are impossible to study from afar.

“Flying so close to the Sun, Parker Solar Probe now senses conditions in the magnetically dominated layer of the solar atmosphere – the corona – that we never could before,” said Nour Raouafi, the Parker project scientist at the Johns Hopkins Applied Physics Laboratory in Laurel, Maryland. “We see evidence of being in the corona in magnetic field data, solar wind data, and visually in images. We can actually see the spacecraft flying through coronal structures that can be observed during a total solar eclipse.”

Closer Than Ever Before

Parker Solar Probe launched in 2018 to explore the mysteries of the Sun by traveling closer to it than any spacecraft before. Three years after launch and decades after first conception, Parker has finally arrived.

Unlike Earth, the Sun doesn’t have a solid surface. But it does have a superheated atmosphere, made of solar material bound to the Sun by gravity and magnetic forces. As rising heat and pressure push that material away from the Sun, it reaches a point where gravity and magnetic fields are too weak to contain it.

That point, known as the Alfvén critical surface, marks the end of the solar atmosphere and beginning of the solar wind. Solar material with the energy to make it across that boundary becomes the solar wind, which drags the magnetic field of the Sun with it as it races across the solar system, to Earth and beyond. Importantly, beyond the Alfvén critical surface, the solar wind moves so fast that waves within the wind cannot ever travel fast enough to make it back to the Sun – severing their connection.

Until now, researchers were unsure exactly where the Alfvén critical surface lay. Based on remote images of the corona, estimates had put it somewhere between 10 to 20 solar radii from the surface of the Sun – 4.3 to 8.6 million miles. Parker’s spiral trajectory brings it slowly closer to the Sun and during the last few passes, the spacecraft was consistently below 20 solar radii (91 percent of Earth’s distance from the Sun), putting it in the position to cross the boundary – if the estimates were correct.

On April 28, 2021, during its eighth flyby of the Sun, Parker Solar Probe encountered the specific magnetic and particle conditions at 18.8 solar radii (around 8.1 million miles) above the solar surface that told scientists it had crossed the Alfvén critical surface for the first time and finally entered the solar atmosphere.

“We were fully expecting that, sooner or later, we would encounter the corona for at least a short duration of time,” said Justin Kasper, lead author on a new paper about the milestone published in Physical Review Letters, and deputy chief technology officer at BWX Technologies, Inc. and University of Michigan professor. “But it is very exciting that we’ve already reached it.”

Into the Eye of the Storm

During the flyby, Parker Solar Probe passed into and out of the corona several times. This is proved what some had predicted – that the Alfvén critical surface isn’t shaped like a smooth ball. Rather, it has spikes and valleys that wrinkle the surface. Discovering where these protrusions line up with solar activity coming from the surface can help scientists learn how events on the Sun affect the atmosphere and solar wind.

At one point, as Parker Solar Probe dipped to just beneath 15 solar radii (around 6.5 million miles) from the Sun’s surface, it transited a feature in the corona called a pseudostreamer. Pseudostreamers are massive structures that rise above the Sun’s surface and can be seen from Earth during solar eclipses.

Passing through the pseudostreamer was like flying into the eye of a storm. Inside the pseudostreamer, the conditions quieted, particles slowed, and number of switchbacks dropped – a dramatic change from the busy barrage of particles the spacecraft usually encounters in the solar wind.

For the first time, the spacecraft found itself in a region where the magnetic fields were strong enough to dominate the movement of particles there. These conditions were the definitive proof the spacecraft had passed the Alfvén critical surface and entered the solar atmosphere where magnetic fields shape the movement of everything in the region.

The first passage through the corona, which lasted only a few hours, is one of many planned for the mission. Parker will continue to spiral closer to the Sun, eventually reaching as close as 8.86 solar radii (3.83 million miles) from the surface. Upcoming flybys, the next of which is happening in January 2022, will likely bring Parker Solar Probe through the corona again.

“I’m excited to see what Parker finds as it repeatedly passes through the corona in the years to come,” said Nicola Fox, division director for the Heliophysics Division at NASA Headquarters. “The opportunity for new discoveries is boundless.”

The size of the corona is also driven by solar activity. As the Sun’s 11-year activity cycle – the solar cycle – ramps up, the outer edge of the corona will expand, giving Parker Solar Probe a greater chance of being inside the corona for longer periods of time.

“It is a really important region to get into because we think all sorts of physics potentially turn on,” Kasper said. “And now we’re getting into that region and hopefully going to start seeing some of these physics and behaviors.”

Narrowing Down Switchback Origins

Even before the first trips through the corona, some surprising physics was already surfacing. On recent solar encounters, Parker Solar Probe collected data pinpointing the origin of zig-zag-shaped structures in the solar wind, called switchbacks. The data showed one spot that switchbacks originate is at the visible surface of the Sun – the photosphere.

By the time it reaches Earth, 93 million miles away, the solar wind is an unrelenting headwind of particles and magnetic fields. But as it escapes the Sun, the solar wind is structured and patchy. In the mid-1990s, the NASA-European Space Agency mission Ulysses flew over the Sun’s poles and discovered a handful of bizarre S-shaped kinks in the solar wind’s magnetic field lines, which detoured charged particles on a zig-zag path as they escaped the Sun. For decades, scientists thought these occasional switchbacks were oddities confined to the Sun’s polar regions.

In 2019, at 34 solar radii from the Sun, Parker discovered that switchbacks were not rare, but common in the solar wind. This renewed interest in the features and raised new questions: Where were they coming from? Were they forged at the surface of the Sun, or shaped by some process kinking magnetic fields in the solar atmosphere?

The new findings, in press at the Astrophysical Journal, finally confirm one origin point is near the solar surface.

The clues came as Parker orbited closer to the Sun on its sixth flyby, less than 25 solar radii out. Data showed switchbacks occur in patches and have a higher percentage of helium – known to come from the photosphere – than other elements. The switchbacks’ origins were further narrowed when the scientists found the patches aligned with magnetic funnels that emerge from the photosphere between convection cell structures called supergranules.

In addition to being the birthplace of switchbacks, the scientists think the magnetic funnels might be where one component of the solar wind originates. The solar wind comes in two different varieties – fast and slow – and the funnels could be where some particles in the fast solar wind come from.

“The structure of the regions with switchbacks matches up with a small magnetic funnel structure at the base of the corona,” said Stuart Bale, professor at the University of California, Berkeley, and lead author on the new switchbacks paper. “This is what we expect from some theories, and this pinpoints a source for the solar wind itself.”

Understanding where and how the components of the fast solar wind emerge, and if they’re linked to switchbacks, could help scientists answer a longstanding solar mystery: how the corona is heated to millions of degrees, far hotter than the solar surface below.

While the new findings locate where switchbacks are made, the scientists can’t yet confirm how they’re formed. One theory suggests they might be created by waves of plasma that roll through the region like ocean surf. Another contends they’re made by an explosive process known as magnetic reconnection, which is thought to occur at the boundaries where the magnetic funnels come together.

“My instinct is, as we go deeper into the mission and lower and closer to the Sun, we’re going to learn more about how magnetic funnels are connected to the switchbacks,” Bale said. “And hopefully resolve the question of what process makes them.”

Now that researchers know what to look for, Parker’s closer passes may reveal even more clues about switchbacks and other solar phenomena. The data to come will allow scientists a glimpse into a region that’s critical for superheating the corona and pushing the solar wind to supersonic speeds. Such measurements from the corona will be critical for understanding and forecasting extreme space weather events that can disrupt telecommunications and damage satellites around Earth.

“It’s really exciting to see our advanced technologies succeed in taking Parker Solar Probe closer to the Sun than we’ve ever been, and to be able to return such amazing science,” said Joseph Smith, Parker program executive at NASA Headquarters. “We look forward to seeing what else the mission discovers as it ventures even closer in the coming years.”

Parker Solar Probe is part of NASA’s Living with a Star program to explore aspects of the Sun-Earth system that directly affect life and society. The Living with a Star program is managed by the agency’s Goddard Space Flight Center in Greenbelt, Maryland, for NASA’s Science Mission Directorate in Washington. The Johns Hopkins University Applied Physics Laboratory in Laurel, Maryland, manages the Parker Solar Probe mission for NASA and designed, built, and operates the spacecraft.

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]]> Can’t find that file? Microsoft’s new Loop app puts workplace collaboration in a different light. https://palmacedar.com/blog/cant-find-that-file-microsofts-new-loop-app-puts-workplace-collaboration-in-a-different-light/?utm_source=rss&utm_medium=rss&utm_campaign=cant-find-that-file-microsofts-new-loop-app-puts-workplace-collaboration-in-a-different-light Tue, 23 Nov 2021 10:46:43 +0000 https://palmacedar.com/?page_id=12043

Microsoft is aiming to solve a long-irritating problem that seemed to become more irksome as people began working remotely during the pandemic: Hunting through hard drives and cloud drives for the correct files – and gathering all of that information in one place where teams can work on them together.

During its Ignite technology conference on Tuesday, the company introduced Microsoft Loop, a new component of its Microsoft 365 suite of productivity apps. Loop allows users and teams to collect everything needed for a project – files, links and data from other apps – into a single workspace, then provide a bird’s eye view of everything happening with a project.

Microsoft also announced an AI-driven feature of Office 365 called Context IQ. It uses the Microsoft Graph – which tracks connections among files, apps and people – to observe what people are working on throughout the day, then predict and suggest what information they need.

In a blog post, Microsoft said the feature is designed to provide relevant files, documents, calendar times and other information “right when you need it – at the point of action.” The feature, Microsoft said, aims to use AI to augment “human capability in ways that feel like magic.”

As long as there have been PCs, knowledge workers have complained of wasted time spent searching for the right information across an array of devices and file directories. The problem has worsened over the last decade with the advent of cloud apps and drives.

A study by Qatalog and Cornell University’s Ellis Idea Lab released in July showed more than 56% of workers said they struggle to keep track of information across all the productivity platforms their companies use. Those same workers said they waste an hour each day searching for what they need. That’s five hours of wasted time each week. Eighty-nine percent said their work lives have gotten worse because of “digital chaos.”

In addition, switching between apps to find the right components of a project – a file, an email, a slice of data – is widely believed to scatter workers’ focus and reduce overall productivity. Psychologist Gerald Weinberg wrote in his book, “Quality Software Management: Systems Thinking,” that this necessary evil, known as “context switching,” devours between 20% and 80% of a workers’ overall productivity.

Microsoft, a top provider of enterprise productivity software, has seen increased competition in recent years from an ever-growing category of cloud-based project management apps such as Asana, Wrike, Basecamp and Monday.com, each of which seek to solve the frustration.

The project management software market alone had grown to $5.37 billion in 2020 and is expected to nearly double to $9.81 billion over the next five years, according to Mordor Intelligence.

Microsoft said its new Loop app, which can follow users across Microsoft’s productivity apps, is made up of three elements: “Loop components,” “Loop pages” and “Loop workspaces.”

“Loop components” are “atomic units of productivity” that let people complete work together right within chats, meetings, emails and documents.

People can use Microsoft’s readymade Loop components or create their own. There’s a voting table that makes it easy for teams to brainstorm or reach decisions together. Team members can also set up “status trackers” to monitor a project’s progress.

Microsoft says Loop pages are like a “flexible canvas” where all those files, links and data for a single project – or piece of a project – can be at the ready. Loop workspaces are broader shared spaces where team members can see what each other are working on, react to each other’s ideas and track progress toward goals.

Loop will work across Microsoft 365 apps like Outlook, Teams and OneNote and will begin rolling out before year’s end, Microsoft said.

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]]> Five Ways Artificial Intelligence Could Shape Our Lives https://palmacedar.com/blog/five-ways-artificial-intelligence-could-shape-our-lives/?utm_source=rss&utm_medium=rss&utm_campaign=five-ways-artificial-intelligence-could-shape-our-lives Mon, 15 Nov 2021 12:03:59 +0000 https://palmacedar.com/?page_id=12037

Tech evangelists habitually brim with enthusiasm over artificial intelligence’s potential to transform our lives, and the crowds at this year’s Web Summit were no exception.

Here are five uses for AI showcased at one of the world’s largest technology conferences, which returned to Lisbon this week after the 2020 edition was called off due to the pandemic.

Healthcare

When Iker Casillas learned of a start-up that uses AI to better detect irregular heart rhythms, he swiftly signed up as an investor.

The Spanish football legend had suffered a heart attack in 2019, putting a brutal end to his career.

Madrid-based company Idoven analyses data from home heart monitoring kits to track people’s cardiac health — and crucially, to flag up looming problems.

“We are the first company in the world capable of doing it,” its CEO Manuel Marina-Breysse told AFP.

AI is also being used by a growing number of mental health startups.

Woebot, a chatbot which people can use to unburden their anxieties, adapts its responses based on an AI-informed reading of the person’s emotional state.

“If somebody is in distress or they’re really not feeling great, Woebot will invite them to work on it, or just get it off their chest,” explained its founder Alison Darcy, a clinical research psychologist.

Some may find the idea of pouring one’s heart out to a chatbot unnerving, but the Silicon Valley startup points to studies suggesting that people sometimes prefer confiding in a non-judgmental robot.

Cutting waste

AI doesn’t represent a straightforward win for the climate.

Training a single algorithm system can use nearly five times the emissions produced by a car over its lifetime, according to University of Massachusetts researchers.

But AI is also making a wide range of industrial processes more efficient, from cement production to cooling data centres.

It could also be used to reduce the amount of garbage we send to landfill.

British startup Greyparrot uses AI to recognise different types of waste moving down a conveyor belt, picking out recyclables from plastic to glass better than the machines typically used at the moment.

Safer roads

Could AI stop road accidents? Irish startup Provizio is developing technology that uses machine learning to analyse data from sensors attached to a car.

In time, its founder Barry Lunn hopes that will allow emergency braking systems to kick into gear 10 times faster than previously.

Code writing

The age of AI shunning all need for human help, and writing its own computer code, is closer than you may think.

One initiative generating a buzz in Lisbon this week was Copilot, a joint project by software development platform GitHub and research lab OpenAI.

The tool can auto-complete chunks of code, understanding the intentions of the human software engineer.

But New York University researchers suggest the computers still need us: around 40 percent of the time, the code still has bugs in it.

Deepfakes

Recent years have seen growing alarm over deepfake technology, in which stunningly realistic likenesses of living people can be made to act as the creator pleases.

Deepfakes appearing to show actor Tom Cruise went viral this year, prompting fresh questions over whether the technology could be used for fraud or even political manipulation.

Reface, a US startup founded by Ukrainians, wants to use deepfake AI for more playful purposes, allowing the user to swap Justin Bieber’s head, or the Mona Lisa’s, for their own.

But co-founder Ivan Altsybieiev imagines a future where people could mock up entire remakes of their favourite TV shows, starring themselves.

A “future where all content could be personalised”, he told AFP.

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]]> Microsoft passes Apple to become the world’s most valuable company https://palmacedar.com/blog/11998-2/?utm_source=rss&utm_medium=rss&utm_campaign=11998-2 Mon, 01 Nov 2021 09:54:06 +0000 https://palmacedar.com/?page_id=11998

Microsoft passed Apple in market cap on Friday, making it the world’s most valuable publicly traded company, after Apple missed earnings expectations on Thursday.

Microsoft had a market cap of nearly $2.49 trillion at market close, while Apple’s stood at about $2.46 trillion.

Apple reported on Thursday that revenue missed Wall Street expectations in the company’s fiscal fourth quarter, a result of supply chain constraints. CEO Tim Cook told CNBC’s Josh Lipton the revenue shortfall is estimated at $6 billion, but he expects worse supply chain issues in the December quarter.

Sales of iPhones at the company were up 47% year over year but also fell short of analyst expectations. The company’s fourth quarter only included a few days of iPhone 13 sales.

Microsoft beat revenue expectations in its fiscal first quarter, which climbed about 22% year over year. That was the fastest growth since 2018, CNBC previously reported.

Apple was the first company to reach a $1 trillion and $2 trillion market cap. It became the world’s most valuable publicly traded company when it surpassed state oil giant Saudi Aramco in market cap last year.

Microsoft last topped Apple in market cap in 2020 as the coronavirus pandemic wreaked havoc on supply chains. It first closed above a $2 trillion market cap in June after revealing the first major update to Windows in more than five years.

At market close, Microsoft’s stock was up more than 48% year to date, while Apple’s had risen almost 13%.

This news is developing. Please check back for updates

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