Utilizing this technology isn't different from utilizing APIs thanks to the numerous AI platforms driving the revolution. If you're in the business world it's not a bad idea to consider the potential these services can provide.
From 2010 to the end of 2010 We officially entered the age of Artificial Intelligence (AI). Many people are looking at their surroundings and asking, "Huh, did I miss something?" because it doesn't look anything like the hype AI "evangelists" and popular culture has been promoting. There aren't any gigantic metallic squid armies that can destroy and there are no mind games that can play with human-like intellect.
As technology usually can, it has been incorporated into nearly everything we do. It's a beautiful technology, and while it is certainly not intelligent on its own-at at least from a human perspective-its applications, when executed correctly can produce nearly magical outcomes. AI might not be anything that could be life-changing for the average person (just small improvements in everyday life, no matter how big or small) but for companies, it is a huge possibilities for innovation, speed expansion, and more.
Technologies like the use of facial recognition and object recognition speech recognition such as object recognition, facial recognition, speech recognition. promises a far superior customer experiences and a nearly unfair advantage over competitors. This is why every business is either creating the AI division or planning on the same lines. It's not necessary to employ a swarm of PhDs. Artificial Intelligence (or Machine Learning in more precise terms) is now mature to the point where a number of large and small-scale players offer AI services similar to REST APIs.
For just a few dollars all and, in some instances, at no cost, you are able to test these services to determine whether they offer a good ROI for the duration of your business.
When you've completed the service and started using its production version, then the bill per month is something you must be watching closely. AI/ML is basically about processing massive amounts of data through the world's most powerful servers (mostly employ processor chips that are found within graphics cards) Naturally when working with huge amounts of files and huge compute is more expensive.
Don't be misled by me. in the wrong.
My goal is not to criticize these firms or discourage anyone from trying to dip their toes into AI waters. They have their pricing plans in full (or made available on request) and, if they don't they aren't able to do much. Thus, when the usage goes without monitoring (or even worse the automated system has an issue that causes, for instance that server RAM fills with data, and keeps being replicated with every machine that is created to deal with the "load" ), the responsibility-similar to your electric bill, falls on you.
That's quite easy. Most service providers use an alert system in which you can choose a amount which acts as the threshold for alerts (say $500/month). In other words, if your monthly usage exceeds $500 then the system will send texts, emails and other messages to everyone listed in the notification section. This kind of panic is hard to ignore. So, what's the takeaway to take away from the experience? This financial alert system should be among the very first items to learn about. It must also be among the first, perhaps your first item to setup and test. You'll be grateful to me for my advice in the future.
Okay, enough chatter! Here's a checklist of AI platforms I discovered to be impressive and what they can provide.
When it concerns AI, Google is the first name that is the first name that comes to your mind.
And what's the name of the second?
It's not like I'm not able to think of one! Google is the most popular choice in AI chats, and with an excellent reason. Through the years Google has invested maybe billions in dollars to AI research and has a huge pool of talent. A number of its impressive AI projects are widely known, and a look at its most recent projects sends chills down your spine.
Due to their deep knowledge, Google has some of the most reliable APIs available to provide in AI/ML. Let's examine some of their major products.
One of the most significant advancements of AI have been in understanding as well as working in natural language that are written or spoken. Text Analysis API by Google Text Analysis API by Google is extremely powerful and offers options like:
Syntax analysis (analyze the text in question and determine the most important parts)
Analysis of the entity (find invoices' data in documents that are not structured, for instance)
Analysis of sentiment (identify intention, mood and mood. (from spoken or written word)
Multilingual (works with a variety of languages)
If you're eager to learn more about your customer opinions from their chats with support Try it now!
Google offers a specific prediction service if you're using your own models and would like to make predictions based on data that is new. You can even add your own code if you're looking for something that's not standard or even experimental. This service forms part of an extensive service known as AI Platform. AI Platform, which we will be discussing in the next article.
Anyone who works in the field of data or AI recognize how cumbersome and time-consuming each stage of the process may be. To alleviate these issues, Google offers an end-to-end full-featured platform called The AI Platform. It's a fully-managed service that focuses on data science as well as ML and is designed to make the operation that comes with ML and data manipulation as easy as it can be.
If you're working with an unreliable ML setup and you're tired of waiting and hiccups the Google AI Platform might be worth having a take a look.
It's asking too much to list every Google AI/ML feature, anyone interested should go to the official documentation. There's more amazing, exciting, and unexplored information there!
If you have even a small amount of curiosity in the AI field, you'd observed the development of GPT-3. This is an extremely advanced ML model that works with natural languages , and made (has?) all of us worried that the end of the world was coming. The driving force that drives GPT-3 is OpenAI which was created to foster research and collaboration within the AI area -and all openly that is not common in the present day world.
The company was most famously praised by Elon Musk One of the founders. During this time, it was the subject of massive media interest due to it's AI research. One of the most notable examples is the AI gamer which was able to play with and destroy the best DOTA 2 players at the top of their game:
At the time of writing, Elon Musk is no anymore involved in the OpenAI project, and OpenAI isn't "open" as per its fundamental principles. But that's another issue, and you'll find plenty of resources on the subject.
The main point is this: OpenAI has been doing really innovative work in AI particularly in the area of video/text processing, text processing as well as other areas. OpenAI offers a range of AI APIs for their services, and I'm sure you'll be able to imagine a viable usage case for each one of them:
Semantic searchallows the search of text in free-form such as documents in response to a query in the natural language. For instance, if you've got an archive of all chats with customer support you could ask questions such as "show me a list of chats where customers were very angry because of late resolution". This isn't an official instance however, I wanted to clarify the possibilities!
Chatbots: The majority of chatbots in the world today are just massive baskets of regret. The company that chose to implement them regrets later the creator of the bot regrets his creation, and the user who visits the website regrets engaging via the robot . . . you'll get the picture. The OpenAI chat capabilities are much better particularly in the realm of small conversations, sudden changes in conversation, indirect intent and more. While it's not perfect but it does raise the bar to allow chatbots to transform from dull/obnoxious.
Service for customers: If concerned that you'd need to mix the two above services in order to make a feasible user experience for customers, OpenAI has already done this. There's a specific service dedicated to customer service, which includes capabilities of recommendations, search as well as recommendations.
Text generation: Exactly similar to the GPT-3 technology we mentioned in the past, OpenAI offers text-generation capabilities through API. The result is authentic intelligent, intelligent text on almost anything (even bizarre and abstract things) that you can utilize in a variety of ways!
Comprehensive: This service analyzes the text in question and makes a brief summary of it. It's with its own language! It's amazing how much time it can help save and the possibilities for this to be useful is enormous. Email fatigue is an excellent application according to me: simply let the AI reduce messages so that you can get rid of your inbox in just 10 minutes instead of 3 hours!
Additional tools OpenAI is also home to a number of other tools and services that can help in actual usage. For instance, you can convert the results of semantic searches into a spreadsheet that allows for simple analysis. There's also an option to translate texts from one language to another (a quite common need) as well as a variety of other tools.
Although OpenAI has made waves in the AI market recently but access to its APIs isn't as straightforward. It is necessary to be on a waitlist, who is approved at what time, and how are also unanswered. Also, keep in mind that even though these technologies are efficient, they're not yet fully developed. That's why they're labeled "beta" on their entire array of services. However, I'd suggest it's worth putting it to the test and test it out as a pilot.
In terms of cloud services, Microsoft is said to be in the third place (after AWS and Google, which is). However, this doesn't mean the company is in danger; it's got its own unique plan (migrating to existing Windows business) and is racing in its own competition. Although Azure's name Azure is widely known however, what's less well-known the fact that Azure also offers a broad range of services with regards related to services that use AI. Say hello to Azure Cognitive Services!
If you think Microsoft hasn't been doing anything in the AI area, check out this:
Azure Cognitive Services is a fully-fledged AI service that includes almost everything you need to create intelligent, powerful applications. In fact, many of their APIs offer intriguing and more targeted applications, which, I believe is what gives them an edge. This is a brief overview of the most important APIs they offer and the capabilities they have:
Language APIs around what's known as Natural Language Processing in computer science. It's about deriving meaning from, creating as well as working on human language (whether written or spoken). Some interesting capabilities are conversational QnA maker (imagine the possibilities in training/education/hiring! ) and integrating the power of conversation in IoT as well as other gadgets such as sentiment analysis, as well as other information about a text and translation (60plus different languages at the time of this writing) and much more.
Speech APIs: These APIs give applications with the capability of working on human language. Some of the most popular offerings are speech-to-text conversion, text-to-speech transformation, translation of speech as well as speech recognition.
Vision Computer Vision has been the subject of much debate, even though it's not perfect, it's capable enough to be used in situations where a possibility of error is present. The Vision APIs available include features that include analysis of video and images as well as recognition of objects (in video and image) as well as face detection videos indexer (generating metadata using video) and much more.
Decision The Decision API is a set of APIs for general purpose that aid in making better decisions or improving the process you use to make ML-based choices. The capabilities offered by this set include anomaly detection (extremely beneficial for data scientists) Content moderation and personalization services (helps to create personalized, intelligent interactions for your app's users) as well as many other.
The Microsoft of today is radically distinct, and has a distinct goal and focus on cloud services, cloud-based services, and integrated solutions. If you're running a Windows-based enterprise either on-premise or in the cloud-based, integrating Azure Cognitive APIs in your software will make sense.
When discussing cloud-based solutions or infrastructure, it's nearly impossible not to include Amazon Web Services (AWS). I could not find a reliable source, therefore I'm unable to link to it, however, AWS alone holds around 33 percent of the market share. As a developer I'm able to testify to the massive power that it has on various sizes and types of software developers, architects, CTOs and business owners, among others.
If it's a fresh SaaS product, customers are looking to host it on AWS right from the beginning In the event that a user is experiencing issues with stability or scaling they'd like to transfer the service to AWS.
I'm not saying that AWS is the best option for cloud infrastructure however, its array of services and its low-cost approach is unbeatable. If you are planning to incorporate AI/ML into the design of your (new as well as existing) applications is on your wish list there is no way to be wrong using Amazon's AI Services.
This is their pitch for elevators:
AWS provides a variety of powerful features-rich services when it is related to AI/ML. Let's take a brief review of the following:
Polly: Text-to-speech is vital feature in the present particularly since it lets businesses develop authentically "alive", intelligent apps which can converse with an authentic, human-like voice. Amazon Polly is a perfect example of this. While the results aren't the kind of thing you'd imagine (listen for the official sample below and this) It's quite good for the majority of scenarios.
Transcribe is the opposite of Polly changing words into texts. I personally can testify to its efficacy, since I utilized Transcribe as part of one of my projects, to listen to recordings from call centers and create transcripts. The result was very precise (again I don't have any statistics however I'd estimate it was above 95 percent accuracy) It was able to easily recognize different accents, even with background noise. Additionally, the amount of metadata that it generated was overwhelming.
Rekognition: Rekognition is Amazon's service for computer vision (for videos and images). In addition to the basic features such as facial recognition as well as object detection and labeling. It also comes with fascinating capabilities, like content moderation (controlling the content your children can watch via their phones for instance) celebrity recognition and equipment recognition (for workers' safety and security) and much more.
Fraud Detector Fraud is a huge pit that is costing businesses lots of dollars and time each day. This service assists by providing fraud detection features for new accounts as well as guest checkouts and online payments, the abuse of loyalty programs, etc. It is evident that this service will be extremely beneficial to the online commerce ecosystem.
Lex Chatbots your thing but you're bored of the boring, stale chatbots you see all over the place, Lex is the thing to investigate. Lex is a complete chatbot with all the features an advanced chatbot requires and because it's a managed solution, you won't have to worry about hosting servers.
Kendra: Kendra is a document search service, with the exception that the search queries are made in the human language. Kendra appears to have an extensive "expertise" in a few industries. This means that the data you search for comes from one of those industries, your search could be refined for greater accuracy.
There are a few other services AWS has provided however, if I attempt to include them all I'll be out of ink and paper! In addition, if I've learned anything about AWS is that it adheres to Hubble's Law that results in an ever-growing universe. When you're reading this post, their list of AI services could be doubled or 10 times larger! If you're interested in AI, I would suggest you to check out their official site and take a look at the features, capabilities as well as the cost.
Because AWS has the largest market share, there's a good chance you're already on AWS. Maybe you're contemplating moving the infrastructure of your business to AWS? If so, selecting AWS AI Services will allow your apps to connect to different AWS service (think S3, EC2, SNS and so on.) easily and with ease. It's easy to talk to those who've required to manage apps spread across multiple infrastructures, and you'll be fully convinced to stay.
ParallelDots isn't exactly in the way of the businesses on this list thus far. But, they're a unique find , and I think they're worthy of more attention.
Since they are primarily an AI business, they develop very useful tools as well as specific solutions to industry. Most importantly they seem to be a firm believer in quality over quantity. In their product menu they have only four options (at at least, as of) which is why one of them stood out to me due to its general nature and extremely precise. The service we're discussing is their APIs for text analysis.
If you click this page and go down to find a virtual play area, where you can type in any text and check out the AI's ability to analyze by pressing an icon.
The text in the image is the default that they've set in the first place, as it happens. After you press the Analyze button that's green The evaluation of your text according to the various categories will be displayed in the next section (the categories are represented by the buttons).
What is the quality of the API? I considered conducting some tests myself which is why I fed it something less simple -- a bit of prose out of one the contemporary writing classics (for those who are interested it's On the Road by Jack Kerouac and was published the year 1957). Let's look through the prose ourselves first:
How do you feel of it? What do you think it is trying to communicate? What kind of mood do you think it conveys? It's a good idea to stop and consider these questions.
Then I pasted it into the text box, and then hit Analyze. This is what I found:
Overall overall, pretty decent! The prose piece I chose is quite difficult and does not express anything explicit. But, the discerning reader can see a distinct color of anger that is noticeable. This is also the case with what the API indicates as the predominant emotion! The text, however, isn't simply angry, as is evident on the score for confidence of 30.58 percent. The score of close to 20 percent is assigned for "boredom" and "happiness" is also logical since I believe the emotions of these two are present within the words, although they aren't as prevalent as the others. Fear, sadness, excitement . . . and who am i to claim that these elements are not present in the texts? But, the prose writing and understanding are incredibly subjective, so if do not agree with me, that's acceptable.
Personally I was amazed by the ParallelDots service when I looked at different aspects of the analysis. Although it wasn't always on target however, in some instances, it seemed odd also, but as I mentioned earlier in this post the goal isn't 100% accuracy. the aim (and it's probably not even feasible). The ultimate goal is to build a robust AI that allows us to build applications that we've been able to imagine for many years.
Also, is ParallelDots text analysis service right for you?
I'd suggest yes if you only require analysis of text, you require very high precision, and you're satisfied with the lack of care that you get from a prospective customer when you choose from the largest companies in the market.
In the past in the past, IBM's Watson project was an all-powerful AI that could replace human beings at any time and for ever. It was making trailers for movies, beating the most skilled players in Jeopardy and many more. The time was nearing and all were convinced of it in the depths of hearts. Now, fast forward to 2020 and Watson has disappeared from the public eye.
But that doesn't mean that it was a flash-in-the-pan idea that was later discarded. Even though Watson's AI was a bit short of its potential (or maybe it was the result of a PR plan all along perhaps? ), Watson lives on as IBM's brains in their AI solutions for companies.
Here are the main Watson Solutions services: Watson Solutions umbrella:
Watson Assistant program has many elements aimed to improve the customer experience both for the client as well as the agent! Agents can find information quickly to answer questions or queries from customers, as well as tailor their service to their needs, offering precise data and metrics, and draw insights from that data -Watson Assistant Watson Assistant does it all.
RegTech IBM RegTech is a powerful service that is designed to enhance compliance and integrate risk management across all levels of an organisation's activities. In a deeper sense it also targets important problems like fraud in payment as well as financial crime.
Watson Health: Watson Health is a highly skilled AI service that is specifically designed for in the field of healthcare. It assists with data-related issues in research, diagnostic imaging optimization of healthcare plans for quality and cost as well as other things. These are just some of the capabilities.
AIOps: AI + Ops = AIOps, according to IBM. It's a special AI service that helps optimize IT operations. It is true that the IT toolschain as well as IT processes may become so complex and extensive that no solution is able to be implemented at the enterprise level. In these situations, AIOps helps with early problem identification, solution resilience better decision-making and many more.
Watson Media: The Watson Media service is designed to stream live video at a massive scale. The AI component makes it proficient in the creation of captions as well as videos search and video analysis and so on. in real-time. Because security cameras are an example that live stream, Watson Media is a excellent choice in this regard as well to detect threats as well as object recognition.
There are several more AI services provided by IBM which you can read about them all here. IBM is an excellent option to use AI products, though keep in mind that their products and positioning are geared for large-scale to extremely-large companies So make sure that it's an appropriate match.
Rev.ai is one of the AI firms that are committed to creating expertise and performing a few things right. However, they've decided to focus on one thing right. Only one! Speech-to-text conversion. That's all they provide! The only thing they offer is text-to-speech and other kinds of AI/ML.
The result of this excessive, bordering-on-madness obsession? The most precise, and possibly the most accurate of the best. They even provide evidence that they have AI here.
As you can observe, their tests have shown Rev.ai being more accurate than Google's text-to-speech. There are a variety of similar examples on the page (all displayed and compared with beats Google) however, sadly there's no live play area (I am not sure why, does it require lots computer power? Perhaps there's a motive?). However, this doesn't mean that you shouldn't try the API; you are able to sign up for a free account and look over the API as thoroughly as you'd like.
Rev.ai could launch additional services in the near future, and I'm scrambling in an attempt to "fix" this article. However, this isn't the situation today and if you're looking for an uncompromising speech-to-text solution that doesn't loss of quality, Rev.ai deserves your attention.
Wit.ai is an AI platform that offers the most advanced features in speech processing, as well as text processing. Yes, that sounds like every other NLP and text-analysis/transcription service out there, but there's more:
Wit.ai is an open source platform. This means that there's no reason to prevent anyone from learning about their expertise as well as hosting it on your own infrastructure.
Wit.ai isn't just a code dump that's awaited on GitHub. It's an actual API service, too (in terms of HTTP APIs) that is available to anyone who wants to utilize.
This API service is completely free. It's free! In fact, it's cheap that there are there is no pricing plan available.
Wit.ai is designed to be adaptable. Its primary function is to aid users (push your) to create, train, testing, and utilizing ML models.
The last item in the previous list (about the extensibility) requires some clarification So here's what it says: Wit.ai is meant to be a bridge on top of the devices, which takes orders and executes actions. Users can send messages or talks to Wit.ai that can then analyze the message and produce metadata. After it has identified the purpose of what the user wishes to accomplish (look at "intent" in the screenshot above) and how they intend to accomplish it (the other information in the screenshot include the task, date and time) the app sends pertinent instructions and information on the phone.
It is important to note that on the market, Wit.ai has very few capabilities. The idea behind it is to force users to create their own models of ML this can be a bit difficult, but simplified and fun with Wit.ai. This is where its power lies. If you decide to go with the no-cost API take note that there are limits on rate (roughly 200-250 request per min, based on the API's endpoint).
Artificial Intelligence (AI), Machine Learning (ML), Neural Networks models, data Training, prediction . . . These aren't new buzzwords. As with all new technology, once it's stabilized, AI has been commoditized. The platforms mentioned in this article provide the same power to all regardless of whether you're an aspiring company or an industrial-scale behemoth.
Do not forget to look into these courses to gain knowledge about AI.
This is why I am advising users that AI/ML (APIs or not APIs) is not going to, by itself, improve your performance (just like "going social" achieves nothing by itself). Although it is thrilling, AI has created a equal playing field. The rest is entirely up to us.
Next, look into some of the most effective AI frameworks for building modern-day applications.