Many, many prophecies in your Bible describe the world after Jesus Christ returns as being a world filled with happiness!

Did you know that God actually commands us to be happy? And He gives a formula for making you happy in His Bible, which is for the whole world.

God is full of joy! And He is creating us to be like He is, so He wants us to be filled with joy, too. Only those people who have that joy will be in His Family in the future.

But look around, and you see todays world filled with unhappiness and other strong, negative feelings.

Revelation 12:9 says this whole world is deceived. One of the greatest deceptions of all is about how to be happy.

Why are people so deceived about this subject? And how can you be happy?

Let me explain the answer to both of those questions. It is deeply misunderstood, and strongly resisted. I present The Key of David, a weekly television program that reaches millions of potential viewers and is available online, and I have noticed that whenever I cover this subject, we get less response than normal.

Id like to challenge you to think about this subject, to read and study the additional literature we offer on it. We give away all our literature freely because God commands us to do so in Matthew 10:8: Freely you have received, freely give. We have done this for over 80 years. We give over a million dollars worth of free literature every year, yet we always have the income we need to do the Work. God commands us to do certain things in the Bible, and He rewards us immensely for obeying Him.

In John 13, Jesus Christ instructs the disciples about the Passover, which begins the holy day plan of God. For I have given you an example that ye should do as I have done to you (verse 15). You must do things the way Christ does. That includes the holy days, which He kept and He commands us to keep. (Request our free booklet Pagan Holidaysor Gods Holy DaysWhich? to learn about how Gods holy days reveal Gods master plan for human beings. This is truth we need!)

Then notice verse 17: If ye know these things, happy are ye if ye do them. Christ said that following His example and obeying Him will make you happy.

God puts everything on the line. If doing these things doesnt make you happy, then that would make God a liar. But He doesnt lieHe cannot lie! (Titus 1:2).

Here is another scripture that describes how happy we can be: But unto you that fear my name shall the Sun of righteousness arise with healing in his wings; and ye shall go forth, and grow up as calves of the stall (Malachi 4:2). Here is a picture of a young calf in the stall that has been born recently and is jumping around because its so thrilled to be alive! And this tells you how to have such abundant lifehow to be happy, and bright and shining like the sun! It starts with fearing God.

Notice verse 4: Remember ye the law of Moses my servant, which I commanded unto him in Horeb for all Israel, with the statutes and judgments. The main law Moses received on Mount Horeb (another name for Mount Sinai), was the Ten Commandments (Exodus 20). And the statutes we are here commanded to remember include the holy days.

The first five books of the Bible are referred to in Scripture as the Law (e.g. Luke 24:44). Those five books are the foundation of the entire Bibleand the Ten Commandments are the center of that foundation. Remember that law! Dont forget it, because keeping it will make you happy!

The book of Malachi shows that most of Gods own people in this end time95 percenthave turned away from that law (e.g. Malachi 2:8-9; 3:7, 14). And here at the end of the book God is saying, Remember this! Remember that law of Moses that he received on Mount Sinai with thunder and lightning, with the mountain and the earth shaking!

In the days of the second temple construction, the Jews who had returned to Jerusalem from captivity had renewed appreciation for the law of God. Nehemiah 8 records them gathering to observe the Feast of Trumpets, and then the Feast of Tabernacles, two of Gods seven annual festivals.

When they gathered, Ezra and the spiritual leaders read the Law to the people. So they read in the book in the law of God distinctly, and gave the sense, and caused them to understand the reading (verse 8). They really made it plain. And how did the people respond? [A]ll the people wept, when they heard the words of the law (verse 9). They were convicted and repentant. That may seem like the opposite of happinessbut in reality, it is the only true path to real happiness!

Nehemiah saw their response. Then he said unto them, Go your way, eat the fat, and drink the sweet, and send portions unto them for whom nothing is prepared: for this day is holy unto our Lord [referring to the Feast of Tabernacles]: neither be ye sorry; for the joy of the Lord is your strength (verse 10). If you are keeping those holy days, God says it will fill you with joy, and that is your strength! Obedience to Gods law makes you strong!

Verse 17 says that they celebrated this festival properly as they hadnt done for generations, and there was very great gladness. That is what keeping Gods law brings.

Many scriptures show that very shortly, Jesus Christ will return to Earth and apply that law, and the Earth will become a paradise, filled with happy and joyful peopleadults, children, everybody. The Almighty God will ensure that this happens!

Jesus Christ continually spoke of the importance of the law and the Old Testament as a whole. He corrected many people for not believing and obeying the law and the Old Testament prophets. The Jews boasted that they followed the law scrupulously. But Moses wrote the Bibles first five books, called the Law, and in John 5:46-47, Jesus told them, Had you believed Moses, you would have believed me, for he wrote of me. But if ye believe not his writings, how shall ye believe my words?

Jesus confirmed the veracity of the Bibles record of the Flood (Matthew 24:37-39; Luke 17:26-27). He confirmed the account of the overthrow of Sodom and Gomorrah (Matthew 10:15; Luke 17:29). He corroborated the fate of Lots wife (Luke 17:32).

After Jesus was crucified and resurrected, He spent some time with His disciples, teaching them. And beginning at Moses and all the prophets, he expounded unto them in all the scriptures the things concerning himself (Luke 24:27). He went through the first five books, throughout the Law, and all the prophets, including the former prophets, the major and minor prophetsand taught them just how relevant and significant it all was! Many people dismiss these sections of the Biblebut Christ certainly didnt!

I saw one commentary that drew together all these examples showing just how much Christ underscored the importance of the Old Testament. But do you know what this commentary did not say? It didnt say what Christ said about the law, the foundation of the entire Bible! This commentary said nothing of that because most of them believe the law has been done away. But what did Christ say? You would think such an important subject would have been mentioned above some of those other miraculous events.

Christ told His disciples, Ye are the light of the world. A city that is set on an hill cannot be hid (Matthew 5:14). Those people who are obeying Him, Christ calls the light of the world! If you are a light to the world, that means you are shining and happy! People will see it! Neither do men light a candle, and put it under a bushel . Let your light so shine before men that they may see your good works, and glorify your Father which is in heaven (verses 15-16). Wow! Let that light shine, and people will see your good works and glorify God!

Now, notice this amazing scripture that is so contrary to what nearly every commentary will tell you: Think not that I am come to destroy the law, or the prophets: I am not come to destroy, but to fulfil (verse 17). He is talking about the Ten Commandments above all. But also the first five books of the Bible and all the prophetic books. He didnt come to destroy these, but to fulfill themto fill them to the full!

For verily I say unto you, Till heaven and earth pass, one jot or one tittle shall in no wise pass from the law, till all be fulfilled (verse 18).

This is the perfect Son of God talking! He said He would cross every T and dot every I of the law in every little detail. He came to fill the law to the full perfectly! Most people in the so-called Christian world talk about the law being done away. But that is the opposite of what Jesus Christ taught!

The Ten Commandments are the foundation of the Bible and are the heart of everythingif you want to be happy. Yet the way the world views it, if youre keeping the law, you are in bondage! What a deception! And look at how unhappy, miserable and dangerous this world is as a result!

Look at how politicians and political adversaries hate each other today. Gods law says you must love your neighbor(Leviticus 19:18). Christ confirmed that this even means loving your enemies (Matthew 5:44). They often talk about how religious they are, but they have such hate in their lives! Harboring such hate means they are not doing what Christ commanded. That is what your Bible says!

God says through the Prophet Isaiah, For the leaders of this people cause them to err; and they that are led of them are destroyed (Isaiah 9:16). The leaders and scholars of Israel should be an example to the whole world, and would be, if they were obeying God. But they have rebelled against God. They are causing people to err and leading people to destruction, spiritually and even physically. Isaiah 3:12 concurs: Those leaders cause thee to err. God emphasizes this! Watch out, because people are leading you astray, causing you to make serious mistakes! Their lawless approach is making you unhappy, and they make God unhappy by what they are doing!

Christ said if you are obeying the law, you will be like the sun, shining with happiness so people can see! You wont be hating peopleyou will love them and be giving to them in any way you can.

The Apostle Paul also strongly endorsed the Old Testament. He explicitly backed up its account of Cain and Abel, of Enoch, of Melchizedek and Abraham, of the miracle of the Red Sea, of Israels rebellion by creating a golden calf, of the life of Rahab and the fall of Jericho, and many other historical incidents that most people dismiss as myth.

Paul also underscored the importance of Gods law. In Romans 10:1-3, he talks about people who have a zeal of God, but not according to knowledge. For they being ignorant of Gods righteousness, and going about to establish their own righteousness, have not submitted themselves unto the righteousness of God. How many people fall into that trap? Do you submit to Gods definition of righteousnessas He defines it in His Word and by His lawor do you try to establish your own definition of righteousness?

Verse 4 reads, For Christ is the end of the law for righteousness to every one that believeth. That does not mean that Christ ended the law, as many would have you believe. The word end comes from the Greek word telos, which means a point aimed at. When you look at Christs example, you see up close what real righteousness looks like, and what God and Christ are all about. If you keep the law the way God directs you to, and you are doing it spirituallythen in the end, you will have the very character of Christ! You will be following His example (1 Peter 2:21), you will have His mind (Philippians 2:5), and you will be keeping the law of love!

1 John 5:3 says, For this is the love of God, that we keep his commandments: and his commandments are not grievous. Gods commands are not grievous, as so many people say they are. They make you happy! And they fill you with love and many other wonderful virtues!

Paul got to the heart of peoples problem with Gods law. He wrote, Because the carnal mind is enmity [or hostile] against God: for it is not subject to the law of God, neither indeed can be (Romans 8:7). You see this natural hostility to God everywhere! And if you are honest, you can even detect it, at least to some degree, within yourself.

The only way we can obey God and keep His law is by receiving His Holy Spirit!

Paul referred repeatedly back to Adam and Eve in his epistles (e.g. Romans 5:14; 1 Corinthians 15:22; 1 Timothy 2:13-14). He spoke about the Garden of Eden and the first two human beings disobeying God and rejecting the tree of life. God kicked them out of the garden, and mankind has followed their example ever since. They rebelled against God and set the example for this world, so God condemned this world to 6,000 years of being cut off from Him.

Now we are very close to the time when Jesus Christ will return. Mankind has had his six days of the weekeach day symbolizing a thousand years (2 Peter 3:8)and the seventh, the Sabbath, is almost here. The Fourth Commandment tells us to keep the Sabbath holy each week (Exodus 20:8-11)and He even says He will bless us with delight and abundance for doing so (Isaiah 58:13-14)but most people ignore that and rebel. The Sabbath points to the fact that Christ is about to use that seventh daythat seventh thousand-year periodto fill this world with happiness and joy! Many scriptures tell us this. Do you believe them?

God tells us we must be doers of the Word (James 1:22-25). You have to do something. Verse 25 says, But whoso looketh into the perfect law of liberty, and continueth therein, he being not a forgetful hearer, but a doer of the work [or this law], this man shall be blessed in his deed.

Do you see Gods law as a law of liberty? If you keep it, you will have freedom. Youll be blessed in special ways by God, and one of those blessings is youll be happy! That is what freedom brings. How can you be happy without freedom? People in this world think they have freedom, but they are really in bondage to sin.

Where there is no vision, the people perish: but he that keepeth the law, HAPPY is he (Proverbs 29:18). Keeping the law gives you vision, and it makes you happy. It shows you how to make things work out in your life, and how to solve your problems. Keep the law, and you have vision: You know where you are going, and you know where God is taking every one of us.

Your life can be filled with happiness, joy and great purpose. That doesnt mean you wont have trials and tests, but the Bible tells us to rejoice even when you have fiery trials, because God is using those to build His very character within you! (e.g. James 1:2-4). He is preparing you for a spectacular eternal future in the very Family of God!

If you want to be happy, God shows you how: He says you must turn from your iniquities (Daniel 9:13)and turn to that law of love, that law of happiness, that law of freedom, that law of joy! Christ came so you could have life, and have it more abundantly (John 10:10). God wants you to be filled with joy, and to live the abundant life! His law shows you the way.

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KT zu Guttenberg, Artificial Intelligence and You - theTrumpet.com

AI Helping to commercialize space

Even before modern computers became a reality, science fiction gave us a plethora of examples of artificial intelligence and smart robots in the context of outer space. From Hal in 2001: A Space Odyssey and the computer on Star Trek to C3PO and R2D2 in Star Wars and even the fantastic machines in Hitchhikers Guide to the Galaxy, it seems that AI and space go together. While those examples are fiction, we are indeed starting to see examples in the real world where we are using artificial intelligence to help commercialize space.

AI Assisting in the Manufacturing of Satellites and Spacecraft

Satellites and spacecraft are complex and expensive pieces of equipment to put together. Within the spacecraft manufacturing operations, there are repetitive and complex tasks that need to be done with exacting measures of precision and often must be done in clean rooms with little exposure to potential contamination. AI-enabled systems and robotics are being used to help the manufacturing process and take away some of the tasks that humans currently do so that humans can focus on the parts that computers cant assemble.

When working to assemble satellites, not only can AI help to physically speed up the process but it can analyze the process itself to see if there are ways the process can be improved. In addition, the AI is also able to look at the work that has been performed and ensure that everything is done properly. Furthermore, the use of collaborative robots (cobots) as part of the manufacturing process are helping to reduce the need for human workers in clean rooms, and make more reliable manufacturing steps that can be error-prone.

AI-enhanced imagery

Satellites are generating thousands, if not millions, of images every minute of the day. Satellites process about 150 terabytes of data everyday. These images capture everything from weather and environmental imagery and data to images down to just inches of every inch of the globe. Capturing images of Earth automatically introduces a number of challenges and opportunities where AI is helping. Without AI, humans are mostly responsible for interpreting, understanding, and analyzing imagery. By the time a human gets around to interpreting an image, you may have to wait for the satellite to move back around to the same position to further refine image analysis.

The power of deep learning and AI-enabled recognition provides significant power in analyzing images and providing ability to review the millions of images produced by spacecraft. Artificial intelligence on the other end can analyze the images as they are being taken and determine if there are any issues with the images. Unlike humans, AI does not need to sleep or take breaks so it can rapidly process a lot of data. Using AI to capture images of Earth also prevents the need for large amounts of communication to and from Earth to analyze photos and determine whether a new photo needs to be taken. By cutting back on communication, the AI is saving processing power, reducing battery usage, and speeding up the image gathering process.

Satellites are also being used to analyze natural disasters from space. Detailed imagery from a satellite can help those on the ground to see victims, determine the course of the disaster, and more. Artificial intelligence is being used to help speed up the response of satellites to natural disasters. With the help of the onboard AI, satellites are able to determine where a natural disaster is located and navigate to that location. They are also able to automate the image gathering process so that the computer does not have to wait for a human in order to have a quick response.

AI systems are even being used to help analyze data collected from probes heading into deep space to see if they are capable of supporting life. The AI looks at patterns in worlds to help determine if they are habitable or might have some form of life existing on them. Potential planets are then sent to humans for further review.

Monitor the Health of Satellites

Satellites are complex pieces of equipment to operate. There are many potential problems that could arise, from equipment malfunctions to collisions with other satellites. In order to help keep satellites functioning properly, AI is used to monitor the health of satellites. AI can keep constant watch on sensors and equipment, provide alerts, and in some cases, carry out corrective action. SpaceX for example, uses AI to keep its satellites from colliding with other objects in space.

AI is also used to control the navigation of satellites and other spacecraft. The AI is able to look at the patterns of other satellites, planets, and space debris. Once the AI has found the patterns, it is able to change the path of the craft to avoid any collisions. While this is proving powerful, some AI experts have concerns about the potential vulnerability or failure of these systems. Experts believe that with AI navigation installed on a spacecraft, that the craft becomes more vulnerable. Turning to AI for cybersecurity and craft health monitoring can help to counteract this though.

In addition to keeping spacecraft operational, communicating between Earth and space can be challenging. Depending on the state of the atmosphere, interference from other signals and the environment, there may be a lot of communications difficulties that a satellite needs to overcome. AI is now being used to help control satellite communication to overcome any transmission problems. These AI-enabled systems are able to determine the amount of power and frequencies that are needed to transmit data back to Earth or to other satellites. With an AI onboard, the satellite is constantly doing this so that signals can get through as the satellite continues in its orbit.

Even spacecraft on other planets or deep in space are using AI in their operation, such as the Mars rovers currently operating on the red planet. On a recent AI Today podcast, NASA Jet Propulsion Laboratory (JPL) chief Tom Soderstrom shared insights into how AI is being used for the Mars rovers, spacecraft, and operations at facilities across the world.

AI on the mars rover is used to help it navigate the planet. The computer is able to make multiple changes to the rovers course every minute. Technology behind the Mars rovers are very similar to that used by self-driving cars. The major difference is that the rover has to navigate more complicated terrain and does not have other vehicular or pedestrian traffic to take into account. That complicated terrain is analyzed by the computer vision systems in the rover as it moves. If a terrain problem is encountered, the autonomous system makes a change to the course of the rover to avoid it or adjust navigation.

AI and Space: Made for Each Other

Over the last few years we have continued to see a large effort to commercialize space. Several companies are even looking to start tourist trips into space. Artificial intelligence is working to make space commercialization a possibility and to make space a safe environment in which to operate. The various benefits of AI in space all work together to enable further venturing into the unknown.

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How Is AI Helping To Commercialize Space? - Forbes

A masterpiece is how then-Deputy Defense Secretary Patrick Shanahan infamously described the Fiscal Year 2020 budget request. It would, he said, align defense spending with the U.S. National Defense Strategy both funding the future capabilities necessary to maintain an advantage over near-peer powers Russia and China, and maintaining readiness for ongoing counter-terror campaigns.

The result was underwhelming. While research and development funding increased in 2020, it did not represent the funding shift toward future capabilities that observers expected. Despite its massive size, the budget was insufficient to address the departments long-term challenges. Key emerging technologies identified by the department such as hypersonic weapons, artificial intelligence, quantum technologies, and directed-energy weapons still lacked a clear and sustained commitment to investment. It was clear that the Department of Defense did not make the difficult tradeoffs necessary to fund long-term modernization. The Congressional Budget Office further estimated that the cost of implementing the plans, which were in any case insufficient to meet the defense strategys requirements, would be about 2 percent higher than department estimates.

Has anything changed this year? The Department of Defense released its FY2021 budget request Feb. 10, outlining the departments spending priorities for the upcoming fiscal year. As is mentioned every year at its release, the proposed budget is an aspirational document the actual budget must be approved by Congress. Nevertheless, it is incredibly useful as a strategic document, in part because all programs are justified in descriptions of varying lengths in what are called budget justification books. After analyzing the 10,000-plus programs in the research, development, testing and evaluation budget justification books using a new machine learning model, it is clear that the newest budgets tepid funding for emerging defense technologies fails to shift the departments strategic direction toward long-range strategic competition with a peer or near-peer adversary.

Regardless of your beliefs about the optimal size of the defense budget or whether the 2018 National Defense Strategys focus on peer and near-peer conflict is justified, the Department of Defenses two most recent budget requests have been insufficient to implement the administrations stated modernization strategy fully.

To be clear, this is not a call to increase the Department of Defenses budget over its already-gargantuan $705.4 billion FY2021 request. Nor is this the only problem with the federal budget proposal, which included cuts to social safety net programs programs that are needed now more than ever to mitigate the effects from COVID-19. Instead, my goal is to demonstrate how the budget fails to fund its intended strategy despite its overall excess. Pentagon officials described the budget as funding an irreversible implementation of the National Defense Strategy, but that is only true in its funding for nuclear capabilities and, to some degree, for hypersonic weapons. Otherwise, it largely neglects emerging technologies.

A Budget for the Last War

The 2018 National Defense Strategy makes clear why emerging technologies are critical to the U.S. militarys long-term modernization and ability to compete with peer or near-peer adversaries. The document notes that advanced computing, big data analytics, artificial intelligence, autonomy, robotics, directed energy, hypersonics, and biotechnology are necessary to ensure we will be able to fight and win the wars of the future. The Government Accountability Office included similar technologies artificial intelligence, quantum information science, autonomous systems, hypersonic weapons, biotechnology, and more in a 2018 report on long-range emerging threats identified by federal agencies.

In the Department of Defenses budget press release, the department argued that despite overall flat funding levels, it made numerous hard choices to ensure that resources are directed toward the Departments highest priorities, particularly in technologies now termed advanced capabilities enablers. These technologies include hypersonic weapons, microelectronics/5G, autonomous systems, and artificial intelligence. Elaine McCusker, the acting undersecretary of defense (comptroller) and chief financial officer, argued, Any place where we have increases, so for hypersonics or AI for cyber, for nuclear, thats where the money went This budget is focused on the high-end fight. (McCuskers nomination for Department of Defense comptroller was withdrawn by the White House in early March because of her concerns over the 2019 suspension of defense funding for Ukraine.) Deputy Defense Secretary David L. Norquist noted that the budget request had the largest research and development request ever.

Despite this, the FY2021 budget is not a significant shift from the FY2020 budget in developing advanced capabilities for competition against a peer or near-peer. I analyzed data from the Army, Navy, Air Force, Missile Defense Agency, Office of the Secretary of Defense, and Defense Advanced Research Projects Agency budget justification books, and the department has still failed to realign its funding priorities toward the long-range emerging technologies that strategic documents suggest should be the highest priority. Aside from hypersonic weapons, which received already-expected funding request increases, most other types of emerging technologies remained mostly stagnant or actually declined from FY2020 request levels.

James Miller and Michael OHanlon argued in their analysis of the FY2020 budget, Desires for a larger force have been tacked onto more crucial matters of military innovation and that the department should instead prioritize quality over quantity. This criticism could be extended to the FY2021 budget, along with the indictment that military innovation itself wasnt fully prioritized either.

Breaking It Down

In this brief review, I attempt to outline funding changes for emerging technologies between the FY2020 and FY2021 budgets based on a machine learning text-classification model, while noting cornerstone programs in each category.

Lets start with the top-level numbers from the R1 document, which divides the budget into seven budget activities. Basic and applied defense research account for 2 percent and 5 percent of the overall FY2021 research and development budget, compared to 38 percent for operational systems development and 27 percent for advanced component development and prototypes. The latter two categories have grown from 2019, in both real terms and as a percentage of the budget, by 2 percent and 5 percent, respectively. These categories were both the largest overall budget activities and also received the largest percentage increases.

Federally funded basic research is critical because it helps develop the capacity for the next generation of applied research. Numerous studies have demonstrated the benefit of federally funded basic science research, with some estimates suggesting two-thirds of the technologies with the most far-reaching impact over the last 50 years [stemmed] from federally funded R&D at national laboratories and research universities. These technologies include the internet, robotics, and foundational subsystems for space-launch vehicles, among others. In fact, a 2019 study for the National Bureau of Economic Researchs working paper series found evidence that publicly funded investments in defense research had a crowding in effect, significantly increasing private-sector research and development from the recipient industry.

Concerns over the levels of basic research funding are not new. A 2015 report by the MIT Committee to Evaluate the Innovation Deficit argued that declining federal basic research could severely undermine long-term U.S. competitiveness, particularly for research areas that lack obvious real-world applications. This is particularly true given that the share of industry-funded basic research has collapsed, with the authors arguing that U.S. companies are left dependent on federally-funded, university-based basic research to fuel innovation. This shift means that federal support of basic research is even more tightly coupled to national economic competitiveness. A 2017 analysis of Americas artificial intelligence strategy recommended that the government [ensure] adequate funding for scientific research, averting the risks of an innovation deficit that could severely undermine long-term competitiveness. Data from the Organization for Economic Cooperation and Development shows that Chinese government research and development spending has already surpassed that of the United States, while Chinese business research and development expenditures are rapidly approaching U.S. levels.

While we may debate the precise levels of basic and applied research and development funding, there is little debate about its ability to produce spillover benefits for the rest of the economy and the public at large. In that sense, the slight declines in basic and applied research funding in both real terms and as a percentage of overall research and development funding hurt the United States in its long-term competition with other major powers.

Clean, Code, Classify

The Defense Departments budget justification books contain thousands of pages of descriptions spread across more than 20 separate PDFs. Each program description explains the progress made each year and justifies the funding request increase or decrease. There is a wealth of information about Department of Defense strategy in these documents, but it is difficult to assess departmental claims about funding for specific technologies or to analyze multiyear trends while the data is in PDF form.

To understand how funding changed for each type of emerging technology, I scraped and cleaned this information from the budget documents, then classified each research and development program into categories of emerging technologies (including artificial intelligence, biotechnologies, directed-energy weapons, hypersonic weapons and vehicles, quantum technologies, autonomous and swarming systems, microelectronics/5G, and non-emerging technology programs). I designed a random forest machine learning model to sort the remaining programs into these categories. This is an algorithm that uses hundreds of decision trees to identify which variables or words in a program description, in this case are most important for classifying data into groups.

There are many kinds of machine learning models that can be used to classify data. To choose one that would most effectively classify the program data, I started by hand-coding 1,200 programs to train three different kinds of models (random forest, k-nearest neighbors, and support vector machine), as well as for a model testing dataset. Each model would look at the term frequency-inverse document frequency (essentially, how often given words appear adjusted for how rarely they are used) of all the words in a programs description to decide how to classify each program. For example, for the Armys Long Range Hypersonic Weapon program, the model might have seen the words hypersonic, glide, and thermal in the description and guessed that it was most likely a hypersonic program. The random forest model slightly outperformed the support vector machine model and significantly outperformed the k-nearest neighbors model, as well as a simpler method that just looked for specific keywords in a program description.

Having chosen a machine-learning model to use, I set it to work classifying the remaining 10,000 programs. The final result is a large dataset of programs mentioned in the 2020 and 2021 research and development budgets, including their full descriptions, predicted category, and funding amount for the year of interest. This effort, however, should be viewed as only a rough estimate of how much money each emerging technology is getting. Even a fully hand-coded classification that didnt rely on a machine learning model would be challenged by sometimes-vague program descriptions and programs that fund multiple types of emerging technologies. For example, the Applied Research for the Advancement of S&T Priorities program funds projects across multiple categories, including electronic warfare, human systems, autonomy, and cyber advanced materials, biomedical, weapons, quantum, and command, control, communications, computers and intelligence. The model took a guess that the program was focused on quantum technologies, but that is clearly a difficult program to classify into a single category.

With the programs sorted and classified by the model, the variation in funding between types of emerging technologies became clear.

Hypersonic Boost-Glide Weapons Win Big

Both the official Department of Defense budget press release and the press briefing singled out hypersonic research and development investment. As one of the departments advanced capabilities enablers, hypersonic weapons, defenses, and related research received $3.2 billion in the FY2021 budget, which is nearly as much as the other three priorities mentioned in the press release combined (microelectronics/5G, autonomy, and artificial intelligence).

In the 2021 budget documents, there were 96 programs (compared with 60 in the 2020 budget) that the model classified as related to hypersonics based on their program descriptions, combining for $3.36 billion an increase from 2020s $2.72 billion. This increase was almost solely due to increases in three specific programs, and funding for air-breathing hypersonic weapons and combined-cycle engine developments was stagnant.

The three programs driving up the hypersonic budget are the Armys Long-Range Hypersonic Weapon, the Navys Conventional Prompt Strike, and the Air Forces Air-Launched Rapid Response Weapon program. The Long-Range Hypersonic Weapon received a $620.42 million funding increase to field an experimental prototype with residual combat capability. The Air-Launched Rapid Response Weapons $180.66 million increase was made possible by the removal of funding for the Air Forces Hypersonic Conventional Strike Weapon in FY2021 which saved $290 million compared with FY2020. This was an interesting decision worthy of further analysis, as the two competing programs seemed to differ in their ambition and technical risk; the Air-Launched Rapid Response Weapon program was designed for pushing the art-of-the-possible while the conventional strike weapon was focused on integrating already mature technologies. Conventional Prompt Strike received the largest 2021 funding request at $1 billion, an increase of $415.26 million over the 2020 request. Similar to the Army program, the Navys Conventional Prompt Strike increase was fueled by procurement of the Common Hypersonic Glide Body that the two programs share (along with a Navy-designed 34.5-inch booster), as well as testing and integration on guided missile submarines.

To be sure, the increase in hypersonic funding in the 2021 budget request is important for long-range modernization. However, some of the increases were already planned, and the current funding increase largely neglects air-breathing hypersonic weapons. For example, the Navys Conventional Prompt Strike 2021 budget request was just $20,000 more than anticipated in the 2020 budget. Programs that explicitly mention scramjet research declined from $156.2 million to $139.9 million.

In contrast to hypersonics, research and development funding for many other emerging technologies was stagnant or declined in the 2021 budget. Non-hypersonic emerging technologies increased from $7.89 billion in 2020 to only $7.97 billion in 2021, mostly due to increases in artificial intelligence-related programs.

Biotechnology, Quantum, Lasers Require Increased Funding

Source: Graphic by the author.

Directed-energy weapons funding fell slightly in the 2021 budget to $1.66 billion, from $1.74 billion in 2020. Notably, the Army is procuring three directed-energy prototypes to support the maneuver-short range air defense mission for $246 million. Several other programs are also noteworthy. The High Energy Power Scaling program ($105.41 million) will finalize designs and integrate systems into a prototype 300 kW-class high-energy laser, focusing on managing thermal blooming (a distortion caused by the laser heating the atmosphere through which it travels) for 300 and eventually 500 kW-class lasers. Second, the Air Forces Directed Energy/Electronic Combat program ($89.03 million) tests air-based directed-energy weapons for use in contested environments.

Quantum technologies funding increased by $109 million, to $367 million, in 2021. In general, quantum-related programs are more exploratory, focused on basic and applied research rather than fielding prototypes. They are also typically funded by the Office of the Secretary of Defense or the Defense Advanced Research Projects Agency rather than by the individual services, or they are bundled into larger programs that distribute funding to many emerging technologies. For example, several of the top 2021 programs that the model classified as quantum research and development based on their descriptions include the Office of the Secretary of Defenses Applied Research for the Advancement of S&T Priorities ($54.52 million), or the Defense Advanced Research Projects Agencys Functional Materials and Devices ($28.25 million). The increase in Department of Defense funding for quantum technologies is laudable, but given the potential disruptive ability of quantum technologies, the United States should further increase its federal funding for quantum research and development, guarantee stable long-term funding, and incentivize young researchers to enter the field. The FY2021 budgets funding increase is clearly a positive step, but quantum technologies revolutionary potential demands more funding than the category currently receives.

Biotechnologies increased from $969 million in 2020 to $1.05 billion in 2021 (my guess is that the model overestimated the funding for emerging biotech programs, by including research programs related to soldier health and medicine that involve established technologies). Analyses of defense biotechnology typically focus on the defense applications of human performance enhancement, synthetic biology, and gene-editing technology research. Previous analyses, including one from 2018 in War on the Rocks, have lamented the lack of a comprehensive strategy for biotechnology innovation, as well as funding uncertainties. The Center for Strategic and International Studies argued, Biotechnology remains an area of investment with respect to countering weapons of mass destruction but otherwise does not seem to be a significant priority in the defense budget. These concerns appear to have been well-founded. Funding has stagnated despite the enormous potential offered by biotechnologies like nanotubes, spider silk, engineered probiotics, and bio-based sensors, many of which could be critical enablers as components of other emerging technologies. For example, this estimate includes the interesting Persistent Aquatic Living Sensors program ($25.7 million) that attempts to use living organisms to detect submarines and unmanned underwater vehicles in littoral waters.

Programs classified as autonomous or swarming research and development declined from $3.5 billion to $2.8 billion in 2021. This includes the Army Robotic Combat Vehicle program (stagnant at $86.22 million from $89.18 million in 2020). The Skyborg autonomous attritable (a low-cost, unmanned system that doesnt have to be recovered after launch) drone program requested $40.9 million and also falls into the autonomy category, as do the Air Forces Golden Horde ($72.09 million), Office of the Secretary of Defenses manned-unmanned teaming Avatar program ($71.4 million), and the Navys Low-Cost UAV Swarming Technology (LOCUST) program ($34.79 million).

The programs sorted by the model into the artificial intelligence category increased from $1.36 billion to $1.98 billion in 2021. This increase is driven by an admirable proliferation of smaller programs 161 programs under $50 million, compared with 119 in 2020. However, as the Department of Defense reported that artificial intelligence research and development received only $841 million in the 2021 budget request, it is clear that the random forest model is picking up some false positives for artificial intelligence funding.

Some critics argue that federal funding risks duplicating artificial intelligence efforts in the commercial sector. There are several problems with this argument, however. A 2017 report on U.S. artificial intelligence strategy argued, There also tends to be shortfalls in the funding available to research and start-ups for which the potential for commercialization is limited or unlikely to be lucrative in the foreseeable future. Second, there are a number of technological, process, personnel, and cultural challenges in the transition of artificial intelligence technologies from commercial development to defense applications. Finally, the Trump administrations anti-immigration policies hamstring U.S. technological and industrial base development, particularly in artificial intelligence, as immigrants are responsible for one-quarter of startups in the United States.

The Neglected Long Term

While there are individual examples of important programs that advance the U.S. militarys long-term competitiveness, particularly for hypersonic weapons, the overall 2021 budget fails to shift its research and development funding toward emerging technologies and basic research.

While recognizing that the overall budget was essentially flat, it should not come as a surprise that research and development funding for emerging technologies was mostly flat as well. But the United States already spends far more on defense than any other country, and even with a flat budget, the allocation of funding for emerging technologies does not reflect an increased focus on long-term planning for high-end competition compared with the 2020 budget. Specifically, the United States should increase its funding for emerging technologies other than hypersonics directed energy, biotech, and quantum information sciences, as well as in basic scientific research even if it requires tradeoffs in other areas.

The problem isnt necessarily the year-to-year changes between the FY2020 and FY2021 budgets. Instead, the problem is that proposed FY2021 funding for emerging technologies continues the previous years underwhelming support for research and development relative to the Department of Defenses strategic goals. This is the critical point for my assessment of the budget: despite multiple opportunities to align funding with strategy, emerging technologies and basic research have not received the scale of investment that the National Defense Strategy argues they deserve.

Chad Peltier is a senior defense analyst at Janes, where he specializes in emerging defense technologies, Chinese military modernization, and data science. This article does not reflect the views of his employer.

Image: U.S. Army (Photo by Monica K. Guthrie)

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Put Your Money Where Your Strategy Is: Using Machine Learning to Analyze the Pentagon Budget - War on the Rocks

The "Innovations in Artificial Intelligence, Predictive Analytics, and BIM" report has been added to ResearchAndMarkets.com's offering.

This edition of IT, Computing and Communications (ITCC) TechVision Opportunity Engine (TOE) provides a snapshot of the emerging ICT led innovations in artificial intelligence, predictive analytics, and building information modelling. This issue focuses on the application of information and communication technologies in alleviating the challenges faced across industry sectors in areas such as retail, agriculture, construction, healthcare, and industrial sectors.

ITCC TOE's mission is to investigate emerging wireless communication and computing technology areas including 3G, 4G, Wi-Fi, Bluetooth, Big Data, cloud computing, augmented reality, virtual reality, artificial intelligence, virtualization and the Internet of Things and their new applications; unearth new products and service offerings; highlight trends in the wireless networking, data management, and computing spaces; provide updates on technology funding; evaluate intellectual property; follow technology transfer and solution deployment/integration; track development of standards and software; and report on legislative and policy issues and many more.

The Information & Communication Technology cluster provides global industry analysis, technology competitive analysis, and insights into game-changing technologies in wireless communication and computing space. Innovations in ICT have deeply permeated various applications and markets.

These innovations have a profound impact on a range of business functions for computing, communications, business intelligence, data processing, information security, workflow automation, quality of service (QoS) measurements, simulations, customer relationship management, knowledge management functions and many more. The global teams of industry experts continuously monitor technology areas such as Big Data, cloud computing, communication services, mobile and wireless communication space, IT applications & services, network security, and unified communications markets. In addition, we also closely look at vertical markets and connected industries to provide a holistic view of the ICT Industry.

Key Topics Covered:

Innovations in Artificial Intelligence, Predictive Analytics, and BIM

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/kmqkj0

View source version on businesswire.com: https://www.businesswire.com/news/home/20200320005350/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Innovations in Artificial Intelligence, Predictive Analytics, and BIM (2019) - ResearchAndMarkets.com - Yahoo Finance

Image used for representational purpose only (Pic: Google Images)

Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumour sensitivity in three advanced non-small cell lung cancer therapies which can help predict more accurate treatment efficacy at an early stage of the disease.

The researchers at Columbia University's Irving Medical Center analysed CT images from 92 patients receiving drug agent nivolumab in two trials; 50 patients receiving docetaxel in one trial, and 46 patients receiving gefitinib in one trial.

To develop the model, the researchers used the CT images taken at baseline and on first-treatment assessment.

"The purpose of this study was to train cutting-edge AI technologies to predict patients' responses to treatment, allowing radiologists to deliver more accurate and reproducible predictions of treatment efficacy at an early stage of the disease," explained Laurent Dercle, associate research scientist at the Columbia University Irving Medical Center.

Radiologists currently quantify changes in tumour size and the appearance of new tumour lesions.

However, this type of evaluation can be limited, especially in patients treated with immunotherapy, who can display atypical patterns of response and progression.

"Newer systemic therapies prompt the need for alternative metrics for response assessment, which can shape therapeutic decision-making," Dercle said in a paper appeared in the journal Clinical Cancer Research.

The researchers used machine learning to develop a model to predict treatment sensitivity in the training cohort.

Each model could predict a score ranging from zero (highest treatment sensitivity) to one (highest treatment insensitivity) based on the change of the largest measurable lung lesion identified at baseline.

"We observed that similar radiomics features predicted three different drug responses in patients with advanced non-small cell lung cancer (NSCLC)," Dercle said.

"With AI, cancer imaging can move from an inherently subjective tool to a quantitative and objective asset for precision medicine approaches," he added.

Link:
Researchers use Artificial Intelligence to predict drug response in lung cancer therapies - EdexLive

The Future of Work

Artificial intelligence is on the horizon and is set to change the way we work. Who will be affected and what skills can you develop to insulate yourself?

We are on the cusp of a potentially historic change. Artificial intelligence, in all its varieties and fields of study, is permeating our society and fundamentally altering how business is performed. Companies large and small are looking to artificial intelligence to fundamentally shift how they do business and how they can stay competitive in today's economy.

Some are questioning whether the potentially transformative changes will all be beneficial to society. They look at what this could mean to employees whose jobs are being displaced by the implementation of human-augmenting technology. Economists are split as to whether these changes will lead to large-scale unemployment or whether this is an evolutionary period for skills in the economy, as was the Industrial Revolution when the agrarian-based economy transitioned to an industrialized one. As we look back, we view this shift in a positive light, but those going through it had the same types of fears and concerns that employees have today.

As an individual, what can you do to make sure you are ready for the future of work?

AI Technologies to Watch

First, it is important to understand what technologies are leading the way for this artificial intelligence revolution and how these technologies impact jobs.

Computer Vision

What is it?

Computer vision is a field of study that teaches computers to see and process what they are seeing. This is accomplished by breaking images down into patterns of pixels and translating these patterns into classifications of objects. Once the computer can categorize what it is looking at, it can use this information to perform follow-on activities. Computer vision is the basis for new technologies such as facial recognition, autonomous vehicles, and visual anomaly detection.

What jobs does it impact?

Jobs that heavily leverage sight as a predominant aspect of their job -- especially when paired with repetitive processing based on what is being seen -- are most at risk of having all or part of their job replaced by computer vision.

Robotic Process Automation

What is it?

Robotic process automation is software that learns from a user's repetitive tasks and can mimic these actions after a period of training. This could include monitoring tasks such as keystrokes and mouse clicks that a user performs. In the background, as this software is monitoring user behavior, it is automatically configuring itself to continue with the same task or similar tasks in perpetuity. This automated processing of repetitive tasks can greatly increase the speed and accuracy of many business processes.

What jobs does it impact?

Jobs that require users to do the same task repeatedly throughout the day are most at risk of having all or part of their job replaced by robotic process automation.

Natural Language Processing

What is it?

Natural language processing includes multiple subfields, each focused on the interpretation and creation of text in a format that is natural to the way we communicate. This includes speech-to-text, text-to-speech, language translation, natural language understanding, and natural language generation. Like the way computer vision uses patterns of pixels to make decisions, natural language processing uses patterns of words to infer meaning and drive decisions from this meaning.

What jobs does it impact?

Jobs that use speech to accept or fulfill orders or provide services are most at risk of having all or part of their job replaced by natural language processing. With natural language generation, jobs involved in the creation of text content are also at great risk of having all or part of their job replaced.

Learning Resilient Attitudes

Given these technologies, what can we do to enhance our skills so we are prepared to evolve our jobs to a higher level as machines and automation replace the repetitive aspects of our work? Here are three approaches that are in high demand today that are resilient because they cannot be easily replaced by artificial intelligence.

Design Thinking

Design thinking is an iterative process that includes understanding users, their behaviors, and their journey through business processes; challenging existing assumptions and constraints that have marred their experience; and redefining problems to identify alternative strategies and solutions. The goal of design thinking is to find solutions that are not instantly apparent with our initial level of understanding of the situation but manifest themselves when patterns are isolated and viewed from different points of view. Design thinking includes empathy with your users, questioning assumptions, brainstorming new ideas, prototyping, and testing solutions.

Growth Mindset

People with a growth mindset subscribe to the theory that failure is not bad but rather is an opportunity to grow. People with this skill and outlook on life view the world differently than those with a fixed mindset. They focus on continuous learning. They learn from failures, feedback, experimentation, and the successes of others. They see challenges less as barriers to success and more as opportunities to discover new abilities to master. Those with a growth mindset don't fear the implementation of artificial intelligence in part of their job -- instead, they look at it as an opportunity to free up time wasted on repetitive tasks and focus on new learning, driving them to higher-value skills.

Digital Dexterity

Digital dexterity is the desire and ability to embrace existing and emerging technologies to achieve better business outcomes. It's a matter of both attitude and skills. This includes understanding how and where artificial intelligence can be implemented in business processes to drive target business objectives. Digital dexterity is tightly aligned with both design thinking and growth mindset and includes the identification and implementation of technology that can transform discovered ideas into reality.

A Final Word

As the economy is on the precipice of a revolutionary shift driven by artificial intelligence, there is significant anxiety and fear among workers. The threat of job loss weighs heavily on society. The best way to free yourself from this burden is to better understand what technologies are involved in this shift and what aspects of existing jobs they most threaten. Apply this knowledge -- acquire the new skills and aptitudes to ensure you do not become a victim of the shifting economy.

About the Author

Troy Hiltbrand is the chief digital officer at Kyni where he is responsible for digital strategy and transformation. You can reach the author at thiltbrand@kyanicorp.com.

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The Future of Work - TDWI

While the market for facial recognition toolsand services is expected to more than double in value to $7bn by 2024, there have been repeated calls by politicians and civil rightsagencies safeguard against potential misuse of the technology. Biometricmonitoring and susceptibility to unfair bias are primary concerns, along withthe lack of industry standards that are a barrier to companies and governmentsdeploying the technologys potential benefits.

To help organizations tackle this challenge, theWorld Economic Forum released the first framework for the safe and trustworthyuse of facial recognition technology. The Framework for ResponsibleLimits on Facial Recognition was built by the Forum, industry actors, policy makers, civil societyrepresentatives and academics. It is meant to be deployed and tested as a toolto mitigate risks from potential unethical practices of the technology.

Although the progress in facial recognitiontechnology has been considerable over the past few years, ethical concerns havesurfaced regarding its limitations, said Kay Firth-Butterfield, Head ofArtificial Intelligence and Machine Learning at the World Economic Forum. Ourambition is to empower citizens and representatives as they navigate thedifferent trade-offs they will face along the way.

This is the first framework to go beyond generalprinciples and to operationalize use cases for two distinct audiences:engineering teams and policy makers. Members of the working group have playedtwo complementary roles:

The first are contributors: industryrepresentatives (Groupe ADP, Amazon Web Services, IDEMIA, IN Groupe,Microsoftand SNCF,); policy makers (members of the French Parliament, OPECST,);academics; civil society organizations; and AFNOR Certification. The second areobservers: the French Data Protection Authority (Commission Nationale delinformatique et des liberts CNIL) and the French Digital Council (ConseilNational du Numrique).

I support the idea of a bill at the FrenchParliament to enable this kind of experiment, which is essential to inform thepublic debate on facial recognition technology, said Didier Baichere, FrenchMP. More specifically, this bill aims to define the scope, objectives,stakeholders, and territories where such an experiment could be conducted aswell as the requirements for an informed and inclusive public consultation topromote public knowledge of the opportunities and the limits of facialrecognition technology.

Recent scientific progress, both in artificialintelligence and in computer vision more specifically, has enabled, in just afew years, a significant breakthrough in areas related to facial recognition,said Jean-Luc Dugelay, computer vision researcher at EURECOM Sophia Antipolis.For that reason, I believe that it is essential to accompany these advances inscience with a global policy reflection on the appropriate use of thistechnology; through a multistakeholder collaboration that involves academics,engineers, technology providers, and users, policy-makers, lawyers andcitizens.

The need for shared landmarks for artificialintelligence in general, and its application for facial recognition inparticular is primordial. Considers Olivier Peyrat, Chief Executive Officer ofAFNOR group. I consider positive all collective initiatives aimed at promotingtransparency, the sharing of the same language, precise and unequivocal, aswell as the definition of measures of confidence. The challenge is to createconditions accepted by public actors, private actors and citizens, to makepossible the development and the implementation of these new technologies in aserene environment.

This framework is structured around four steps:

Define what constitutes the responsible use of facial recognition through thedrafting of a set of principles for action. These principles focus on privacy,bias mitigation, the proportional use of the technology, accountability,consent, right to accessibility, childrens rights and alternative options.

Design best practices, to support product teams in the development of systems thatare responsible by design, focusing on four main dimensions: justify the useof facial recognition, design a data plan that matches end-usercharacteristics, mitigate the risks of biases, and inform end-users.

Assess to what extent the system designed is responsible, through an assessmentquestionnaire that describes what rules should be respected for each use caseto comply with the principles for action

Validate compliance with the principle for action through the design of an auditframework by a trusted third party (AFNOR Certification for the policy pilot).

France joined the World Economic Forum Centrefor the Fourth Industrial Revolution in January 2019. The framework wasco-designed by a fellow from the French government in residence at the Centre.

Related

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The Influence of Artificial Intelligence on Future Education - Modern Diplomacy

NEW YORK: Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumor sensitivity in three advanced non-small cell lung cancer therapies which can help predict more accurate treatment efficacy at an early stage of the disease.

The researchers at Columbia Universitys Irving Medical Center analyzed CT images from 92 patients receiving drug agent nivolumab in two trials; 50 patients receiving docetaxel in one trial; and 46 patients receiving gefitinib in one trial.

To develop the model, the researchers used the CT images taken at baseline and on first-treatment assessment.

The purpose of this study was to train cutting-edge AI technologies to predict patients responses to treatment, allowing radiologists to deliver more accurate and reproducible predictions of treatment efficacy at an early stage of the disease, explained Laurent Dercle, an associate research scientist at the Columbia University Irving Medical Center.

Radiologists currently quantify changes in tumor size and the appearance of new tumor lesions.

However, this type of evaluation can be limited, especially in patients treated with immunotherapy, who can display atypical patterns of response and progression.

Newer systemic therapies prompt the need for alternative metrics for response assessment, which can shape therapeutic decision-making,

Dercle said in a paper appeared in the journal Clinical Cancer Research.

The researchers used machine learning to develop a model to predict treatment sensitivity in the training cohort.

Each model could predict a score ranging from zero (highest treatment sensitivity) to one (highest treatment insensitivity) based on the change of the largest measurable lung lesion identified at baseline.

We observed that similar radionics features predicted three different drug responses in patients with advanced non-small cell lung cancer (NSCLC), Dercle said.

With AI, cancer imaging can move from an inherently subjective tool to a quantitative and objective asset for precision medicine approaches, he added. (IANS)

Also Read: Researchers found Artificial intelligence can improve diagnosis, treatment of sleep disorders

Also Watch:Coronavirus update: Buddhist Monastery in Naharkatika take extra prevention measures

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Artificial Intelligence can better predict drug response to lung cancer therapies - The Sentinel Assam

Founders: Ciarn Tobin, Bart Lehane and Shane LynnElevator pitch: Artificial intelligence for customer serviceFunding: 1.5 million in seed fundingStatus: Customers in banking, insurance and e-commerce

THE FOUNDERS OF artificial intelligence startup EdgeTier might come from technical backgrounds in data science, but that doesnt mean their expertise cant be applied to an everyday problem.

The Dublin business is building artificial intelligence tools that customer service agents to simplify how they deal with queries and access the information they need.

Co-founder and chief executive Shane Lynn admits that EdgeTier has thrown its hat into a crowded space but he and co-founders Ciarn Tobin and Bart Lehane felt they could still offer something unique.

In Ireland there are tens of thousands of people working in customer service, meaning theres an appetite among these companies to improve their processes as much as possible.

We spotted and looked for common problems between the different customer service organisations and thats where the idea for the product that were now building and selling came about, Lynn told Fora.

Still a lot of customer service organisations arent running efficiently. There are people doing things that computers are good at and there are people expecting computers to do things that humans are good at, he said.

Human touch

The best parts of the customer are the human parts, he added, whether thats understanding a complex question, showing empathy for a situation or negotiating a compromise.

Source: Shutterstock/Production Perig

These are human communication traits that a customer service AI cannot fully replicate.

Theyre very hard to fake and theyre very hard to implement with a computer system.

According to Lynn, the push for automation using AI can sometimes expect too much of these systems.

Full automation is not quite there and perhaps wont be for some time if customer service agents want to maintain the human element.

What can be automated is the mundane and repetitive, such as looking up specific data or answering specific questions that have definite answers what time does the store close at? or how much does that product cost?.

All of that work isnt that valuable from a customer experience point of view, it is valuable because it needs to be done but its not really what humans are good at. Humans are good at the communications piece, Lynn said.

EdgeTiers solution, dubbed Arthur, guides the customer service agent to and through the information they need to more accurately assist the customer with their specific query and to address complicated needs that require human understanding.

One example could be in travel, where a customer accidentally double books a journey and wants a refund on one booking but not the other and maybe wants to change one detail while keeping the rest.

Loads of these agents are working and what we want to do is free up their time by letting the computer do the bits that the computers are good at and letting the human concentrate on the actual communication between the business and the customer and get to the nub of the problem.

Next steps

To date, EdgeTier is working with companies in Ireland and the UK as well as a bank in Hungary. Its customers are usually in the travel, e-commerce, insurance and banking sectors.

Source: Conor McCabe Photography Ltd

Its revenue stream is a licensing model based on the number of customer interactions that run through the system.

The startup raised 1.5 million last year to finance its growth push and acquire new customers. The seed round was led by London venture capital firm Episode 1 with participation from Act Venture Capital and Enterprise Ireland.

Lynn said that for companies cutting through the noise in AI hype, the opportunity is significant.

While it sounds cool, its not particularly reliable that an AI is learning from previous agents behaviour because you have no control over what the quality of that behaviour is, he said.

If an AI is simply learning from the customer service agents practices, it may be picking up bad answers too and learning them. As the saying goes, garbage in, garbage out.

We sit down with senior agents and we extract and work with them to embody what is the best practice in these particular instances and hone and fine-tune it, Lynn said. We pick whoever is the top-performing agent and we essentially encapsulate their specific knowledge of the system.

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EdgeTier wants AI to get along with customer service agents rather than replace them - Fora.ie

Dr. Agustin Schiffrin and his team at the School of Physics and Astronomy at Monash University).

FLEET

An Australian-German collaboration has demonstrated fully-autonomous scanning probe microscopy (SPM) operation, applying artificial intelligence and deep learning to remove the need for constant human supervision.

The new system, dubbed DeepSPM, bridges the gap between nanoscience, automation, and artificial intelligence (AI), and firmly establishes the use of machine learning for experimental scientific research.

Image acquired by scanning tunneling microscopy (STM): individual silver atoms on a crystalline metal surface.

FLEET

"Optimizing SPM data acquisition can be very tedious. This optimization process is usually performed by the human experimentalist, and is rarely reported," says ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET) chief investigator Dr. Agustin Schiffrin of Monash University.

"Our new AI-driven system can operate and acquire optimal SPM data autonomously, for multiple straight days, and without any human supervision."

The advance brings advanced SPM methodologies such as atomically-precise nanofabrication and high-throughput data acquisition closer to a fully automated turnkey application.

The new deep learning approach can be generalized to other SPM techniques. The researchers have made the entire framework publicly available online as open source, creating an important resource for the nanoscience research community.

Image acquired by atomic force microscopy (AFM): a single molecule, similar to chlorophyll.

FLEET

"Crucial to the success of DeepSPM is the use of a self-learning agent, as the correct control inputs are not known beforehand," says Dr. Cornelius Krull, project co-leader.

"Learning from experience, our agent adapts to changing experimental conditions and finds a strategy to maintain the system stable," says Krull, who works with Shiffrin at Monash School of Physics and Astronomy.

The AI-driven system begins with an algorithmic search of the best sample regions and proceeds with autonomous data acquisition.

It then uses a convolutional neural network to assess the quality of the data. If the quality of the data is not good, DeepSPM uses a deep reinforcement learning agent to improve the condition of the probe.

DeepSPM can run for several days, acquiring and processing data continuously, while managing SPM parameters in response to varying experimental conditions, without any supervision.

The study demonstrates fully autonomous, long-term SPM operation for the first time by combining:

- This press release was originally published on theARC Centre of Excellence in Future Low-Energy Electronics Technologies website

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Putting Artificial Intelligence to Work in the Lab - Lab Manager Magazine