AI as a boon to MNCs
AI- Artificial Intelligence: Deeply confused with Machine Learning and Deep Learning, In layman’s terms, Consider AI a superset with machine learning as it’s subset and deep learning being the subset of both.
We live in an era where fewer than 10% of the world’s public companies account for more than 80% of all profits, according to the Economist. I collected some data on the top 10 MNCs of the world and 6 of these are Tech Giants. As a part of evolution, these companies use AI to advance and increase their profits.
Apple has an estimated net worth of $605 billion, still it continues selling iPhones without chargers. Well, the new Cinematic L1 Video Stabilization with a Log-Homography Model for stabilizing handheld video that simulates the camera motions cinematographers achieve with equipment like tripods, dollies, and Steadicams. The approach extends the work of Grundmann by solving with full homographies (rather than affinities) in order to correct perspective, preserving linearity by working in log-homography space.
Also, improvement in Human-Labeled Data through Dynamic Automatic Conflict Resolution is a big step for user’s comfort. This does not require a ground truth dataset and is instead based on inter-project annotation inconsistencies. This makes DACR not only more accurate but also available to a broad range of labeling tasks.
2. Alphabet Inc.
->Google LLC, widely known for Internet-related services, which include online advertising technologies, a search engine, cloud computing, software, and hardware. Well, a minor percentage of world’s population know it’s parent company that is, Alphabet Inc.
Google itself is carrying multiple researches in AI in enormous number of domains ranging from:
1. Commerce- showing relatable advertisements, building cloud streaming technology that enables users to see products in augmented reality (AR), Google Lens will let shoppers discover similar products by tapping on elements.
2. Search-Google says it will let users search for songs by simply humming or whistling melodies. Google’s spell-checking feature for Search — will enable more accurate and precise spelling suggestions. Google says the new underlying language model contains 680 million parameters (the variables that determine each prediction) and runs in less than three milliseconds.
3. Data management-Google says users will soon be able to see how busy places are in Google Maps without searching for specific beaches, grocery stores, pharmacies, or other locations, an expansion of Google’s existing busyness metrics.
And, this is just Google.
There are many subsidiaries of Google but of those : X-moonshot technologies, Verily, Jigsaw, Calico, Waymo, and DeepMind(being the most important) use AI as the foundation technology.
It believes, “ AI could be one of humanity’s most useful inventions.”
It mostly works on projects that have an impact on a society.
One of them is predicting whether a person is going to develop vision loss by Age-related macular degeneration.
Next, we have Ferminet-Fermionic Neural Networks.
Now, brace yourselves for a mind blowing approximate calculation. The state of a classical system can be described easily — we just have to track the position and momentum of each particle whereas representing the state of a quantum system is far more challenging. A probability has to be assigned to every possible configuration of electron positions. This is encoded in the wavefunction, which assigns a positive or negative number to every configuration of electrons, and the wavefunction squared gives the probability of finding the system in that configuration. The space of all possible configurations is enormous — if you tried to represent it as a grid with 100 points along each dimension, then the number of possible electron configurations for the silicon atom would be larger than the number of atoms in the universe! Now, that’s why we need a Quantum Supercomputer.
In the FermiNet, this is achieved by making each function going into the determinant a function of all electrons. This goes far beyond methods that just use one- and two-electron functions. The FermiNet has a separate stream of information for each electron. To go beyond this, we average together information from across all streams at each layer of the network, and pass this information to each stream at the next layer. That way, these streams have the right symmetry properties to create an antisymmetric function.
This was a brief overview of how AI might prove to be a boon to human race. These MNCs are earning huge profits working in this field. There are many other MNCs that use AI not in projects but to maximise their Sales or User base like Facebook, Amazon, Spotify- deploying AI to predict and show users the relevant data, So that the users spend time increases.