diff --git a/docs/source/about.rst b/docs/source/about.rst
deleted file mode 100644
index 6a6068b..0000000
--- a/docs/source/about.rst
+++ /dev/null
@@ -1,46 +0,0 @@
-.. _chapter-about:
-
-=====
-About
-=====
-
-Ceres Solver grew out of the need for general least squares solving at Google.
-Around 2010, Sameer Agarwal and Keir Mierle decided to replace a custom bundle
-adjuster at Google with something more modern. After two years of on-and-off
-development, Ceres Solver was released as open source in May of 2012.
-
-Acknowledgements
-----------------
-
-A number of people have helped with the development and open sourcing
-of Ceres.
-
-Fredrik Schaffalitzky when he was at Google started the development of
-Ceres, and even though much has changed since then, many of the ideas
-from his original design are still present in the current code.
-
-Amongst Ceres' users at Google two deserve special mention: William
-Rucklidge and James Roseborough. William was the first user of
-Ceres. He bravely took on the task of porting production code to an
-as-yet unproven optimization library, reporting bugs and helping fix
-them along the way. James is perhaps the most sophisticated user of
-Ceres at Google. He has reported and fixed bugs and helped evolve the
-API for the better.
-
-Since the initial release of Ceres, a number of people have
-contributed to Ceres by porting it to new platforms, reporting bugs,
-fixing bugs and adding new functionality. We acknowledge all of these
-contributions in the :ref:`chapter-version-history`.
-
-Origin of the name Ceres Solver
--------------------------------
-While there is some debate as to who invented the method of Least Squares
-[Stigler]_, there is no debate that it was `Carl Friedrich Gauss
-<http://en.wikipedia.org/wiki/Carl_Friedrich_Gauss>`_ who brought it to the
-attention of the world. Using just 22 observations of the newly discovered
-asteroid `Ceres <http://en.wikipedia.org/wiki/Ceres_(dwarf_planet)>`_, Gauss
-used the method of least squares to correctly predict when and where the
-asteroid will emerge from behind the Sun [TenenbaumDirector]_. We named our
-solver after Ceres to celebrate this seminal event in the history of astronomy,
-statistics and optimization.
-
diff --git a/docs/source/building.rst b/docs/source/building.rst
index 750ecef..700f41a 100644
--- a/docs/source/building.rst
+++ b/docs/source/building.rst
@@ -1,13 +1,19 @@
 .. _chapter-building:
 
-=====================
-Building & Installing
-=====================
+=======================
+Building & Installation
+=======================
 
-Stable Ceres Solver releases are available for download at
-`code.google.com <http://code.google.com/p/ceres-solver/>`_. For the
-more adventurous, the git repository is hosted on `Gerrit
-<https://ceres-solver-review.googlesource.com/>`_.
+Getting the source code
+=======================
+.. _section-source:
+
+You can start with the `latest stable release
+<http://ceres-solver.org/ceres-solver-1.8.0.tar.gz>`_ . Or if you want
+the latest version, you can clone the git repository
+  .. code-block:: bash
+
+       git clone https://ceres-solver.googlesource.com/ceres-solver
 
 .. _section-dependencies:
 
@@ -185,21 +191,36 @@
 
 Building on Mac OS X
 ====================
-
-On OS X, we recommend using the `homebrew
-<http://mxcl.github.com/homebrew/>`_ package manager to install the
-dependencies. There is no need to install ``BLAS`` or ``LAPACK``
-separately as OS X ships with optimized ``BLAS`` and ``LAPACK``
-routines as part of the `vecLib
-<https://developer.apple.com/library/mac/#documentation/Performance/Conceptual/vecLib/Reference/reference.html>`_
-framework.
-
 .. NOTE::
 
  Ceres will not compile using Xcode 4.5.x (Clang version 4.1) due to a bug in that version of
  Clang.  If you are running Xcode 4.5.x, please update to Xcode >= 4.6.x before attempting to
  build Ceres.
 
+
+On OS X, we recommend using the `homebrew
+<http://mxcl.github.com/homebrew/>`_ package manager to install Ceres.
+
+.. code-block:: bash
+
+      brew install ceres-solver
+
+will install the latest stable version along with all the required
+dependencies and
+
+.. code-block:: bash
+
+      brew install ceres-solver --HEAD
+
+will install the latest version in the git repo.
+
+You can also install each of the dependencies by hand using `homebrew
+<http://mxcl.github.com/homebrew/>`_. There is no need to install
+``BLAS`` or ``LAPACK`` separately as OS X ships with optimized
+``BLAS`` and ``LAPACK`` routines as part of the `vecLib
+<https://developer.apple.com/library/mac/#documentation/Performance/Conceptual/vecLib/Reference/reference.html>`_
+framework.
+
 .. code-block:: bash
 
       # CMake
@@ -211,7 +232,6 @@
       # SuiteSparse and CXSparse
       brew install suite-sparse
 
-
 We are now ready to build and test Ceres.
 
 .. code-block:: bash
@@ -223,7 +243,6 @@
    make -j3
    make test
 
-
 Like the Linux build, you should now be able to run
 ``bin/simple_bundle_adjuster``.
 
diff --git a/docs/source/features.rst b/docs/source/features.rst
new file mode 100644
index 0000000..50f22e7
--- /dev/null
+++ b/docs/source/features.rst
@@ -0,0 +1,92 @@
+========
+Features
+========
+.. _chapter-features:
+
+* **Code Quality** - Ceres Solver has been used in production at
+  Google for more than three years now. It is used to solve a wide
+  variety of problems, both in size and complexity. The code runs on
+  Google's data centers, desktops and on cellphones. It is clean,
+  extensively tested and well documented code that is actively
+  developed and supported.
+
+* **Modeling API** - It is rarely the case that one starts with the
+  exact and complete formulation of the problem that one is trying to
+  solve. Ceres's modeling API has been designed so that the user can
+  easily build and modify the objective function, one term at a
+  time. And to do so without worrying about how the solver is going to
+  deal with the resulting changes in the sparsity/structure of the
+  underlying problem. Indeed we take great care to separate the
+  modeling of the optimization problem from solving it. The two can be
+  done more or less completely independently of each other.
+
+  - **Derivatives** Supplying derivatives is perhaps the most tedious
+    and error prone part of using an optimization library.  Ceres
+    ships with `automatic`_ and `numeric`_ differentiation. So you
+    never have to compute derivatives by hand (unless you really want
+    to). Not only this, Ceres allows you to mix automatic, numeric and
+    analytical derivatives in any combination that you want.
+
+  - **Robust Loss Functions** Most non-linear least squares problems
+    involve data. If there is data, there will be outliers. Ceres
+    allows the user to *shape* their residuals using robust loss
+    functions to reduce the influence of outliers.
+
+  - **Local Parameterization** In many cases, some parameters lie on a
+    manifold other than Euclidean space, e.g., rotation matrices. In
+    such cases, the user can specify the geometry of the local tangent
+    space by specifying a LocalParameterization object.
+
+* **Solver Choice** Depending on the size, sparsity structure, time &
+  memory budgets, and solution quality requiremnts, different
+  optimization algorithms will suit different needs. To this end,
+  Ceres Solver comes with a variety of optimization algorithms, some
+  of them the result of the author's own research.
+
+  - **Trust Region Solvers** - Ceres supports Levenberg-Marquardt,
+    Powell's Dogleg, and Subspace dogleg methods. The key
+    computational cost in all of these methods is the solution of a
+    linear system. To this end Ceres ships with a variety of linear
+    solvers - dense QR and dense Cholesky factorization (using
+    `Eigen`_ or `LAPACK`_) for dense problems, sparse Cholesky
+    factorization (`SuiteSparse`_ or `CXSparse`_) for large sparse
+    problems custom Schur complement based dense, sparse, and
+    iterative linear solvers for `bundle adjustment`_ problems.
+
+  - **Line Search Solvers** - When the problem size is so large that
+    storing and factoring the Jacobian is not feasible or a low
+    accuracy solution is required cheaply, Ceres offers a number of
+    line search based algorithms. This includes a number of variants
+    of Non-linear Conjugate Gradients, BFGS and LBFGS.
+
+* **Speed** - Ceres code has been extensively optimized, with C++
+  templating, hand written linear algebra routines and OpenMP based
+  multithreading of the Jacobian evaluation and the linear solvers.
+
+* **Solution Quality** Ceres is the best performing solver on the NIST
+  problem set used by Mondragon and Borchers for benchmarking
+  non-linear least squares solvers.
+
+* **Covariance estimation** - Evaluate the sensitivity/uncertainty of
+  the solution by evaluating all or part of the covariance
+  matrix. Ceres is one of the few solvers that allows you to to do
+  this analysis at scale.
+
+* **Community** Since its release as an open source software, Ceres
+  has developed an active developer community that contributes new
+  features, bug fixes and support.
+
+* **Portability** - Runs on *Linux*, *Windows*, *Mac OS X*, *Android*
+  *and iOS*.
+
+* **BSD Licensed** The BSD license offers the flexibility to ship your
+  application
+
+.. _solution quality: https://groups.google.com/forum/#!topic/ceres-solver/UcicgMPgbXw
+.. _bundle adjustment: http://en.wikipedia.org/wiki/Bundle_adjustment
+.. _SuiteSparse: http://www.cise.ufl.edu/research/sparse/SuiteSparse/
+.. _Eigen: http://eigen.tuxfamily.org/
+.. _LAPACK: http://www.netlib.org/lapack/
+.. _CXSparse: https://www.cise.ufl.edu/research/sparse/CXSparse/
+.. _automatic: http://en.wikipedia.org/wiki/Automatic_differentiation
+.. _numeric: http://en.wikipedia.org/wiki/Numerical_differentiation
diff --git a/docs/source/history.rst b/docs/source/history.rst
new file mode 100644
index 0000000..b159284
--- /dev/null
+++ b/docs/source/history.rst
@@ -0,0 +1,27 @@
+.. _chapter-history:
+
+=======
+History
+=======
+
+Ceres Solver grew out of the need for general least squares solving at
+Google. In early 2010, Sameer Agarwal and Fredrik Schaffalitzky
+started the development of Ceres Solver. Fredrik left Google shortly
+thereafter and Keir Mierle stepped in to take his place. After two
+years of on-and-off development, Ceres Solver was released as open
+source in May of 2012.
+
+Origin of the name
+------------------
+
+While there is some debate as to who invented the method of Least
+Squares [Stigler]_, there is no debate that it was `Carl Friedrich
+Gauss
+<http://www-groups.dcs.st-and.ac.uk/~history/Biographies/Gauss.html>`_
+who brought it to the attention of the world. Using just 22
+observations of the newly discovered asteroid `Ceres
+<http://en.wikipedia.org/wiki/Ceres_(dwarf_planet)>`_, Gauss used the
+method of least squares to correctly predict when and where the
+asteroid will emerge from behind the Sun [TenenbaumDirector]_. We
+named our solver after Ceres to celebrate this seminal event in the
+history of astronomy, statistics and optimization.
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 0dcf5a0..c52af14 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -11,7 +11,7 @@
    :maxdepth: 3
    :hidden:
 
-   introduction
+   features
    building
    tutorial
    modeling
@@ -19,41 +19,43 @@
    faqs
    contributing
    version_history
-   about
+   history
    bibliography
    license
 
-Ceres Solver is an industrial-grade C++ library for modeling and
-solving `nonlinear least squares`_ problems. These problems comes up
-in a broad range of areas across science and engineering - from
-`fitting curves`_ in statistics, to constructing `3D models from
-photographs`_ in computer vision.
+Ceres Solver is an open source C++ library for modeling and solving
+large complicated `nonlinear least squares`_ problems. It is a feature
+rich, mature and performant library which has been used in production
+since 2010. At Google, Ceres Solver is used to:
 
-Ceres Solver features an integrated modeling layer with automatic
-differentiation (you can also use numeric and/or analytic
-derivatives), well optimized code with extensive tests and state of
-the art performance on a variety of problems.
+* Estimate the pose of `Street View`_ cars, aircrafts, and satellites.
+* Build 3D models for `PhotoTours`_.
+* Estmate satellite image sensor characteristics.
+* Stitch `panoramas`_ or apply `Lens Blur`_ on Android.
+* Solve `bundle adjustment`_ and SLAM problems in `Project Tango`_.
 
-Ceres Solver is used in Google `Street View`_, Google `PhotoTours`_,
-Google `PhotoSphere`_, `Project Tango`_, `Blender`_, and more.
+Outside Google, Ceres is used for solving problems in computer vision,
+computer graphics, astronomy and physics. e.g., `Willow Garage`_ uses
+it to solve SLAM problems and `Blender`_ uses it for for planar
+tracking and bundle adjustment.
 
 .. _nonlinear least squares: http://en.wikipedia.org/wiki/Non-linear_least_squares
 .. _fitting curves: http://en.wikipedia.org/wiki/Nonlinear_regression
-.. _3D models from photographs: http://en.wikipedia.org/wiki/Structure_from_motion
+.. _bundle adjustment: http://en.wikipedia.org/wiki/Structure_from_motion
 .. _Street View: http://youtu.be/z00ORu4bU-A
 .. _PhotoTours: http://google-latlong.blogspot.com/2012/04/visit-global-landmarks-with-photo-tours.html
-.. _PhotoSphere: http://www.google.com/maps/about/contribute/photosphere/
+.. _panoramas: http://www.google.com/maps/about/contribute/photosphere/
 .. _Project Tango: https://www.google.com/atap/projecttango/
 .. _Blender: http://mango.blender.org/development/planar-tracking-preview/
+.. _Willow Garage: https://www.willowgarage.com/blog/2013/08/09/enabling-robots-see-better-through-improved-camera-calibration
+.. _Lens Blur: http://googleresearch.blogspot.com/2014/04/lens-blur-in-new-google-camera-app.html
 
 Getting started
 ---------------
 
 * Download the `latest stable release
-  <http://ceres-solver.org/ceres-solver-1.8.0.tar.gz>`_
-  or, for those wanting the latest
-* Clone the development version or `browse the source
-  <https://ceres-solver.googlesource.com/ceres-solver>`_
+  <http://ceres-solver.org/ceres-solver-1.8.0.tar.gz>`_ or clone the
+  Git repository for the latest development version.
 
   .. code-block:: bash
 
diff --git a/docs/source/introduction.rst b/docs/source/introduction.rst
deleted file mode 100644
index d21f7d9..0000000
--- a/docs/source/introduction.rst
+++ /dev/null
@@ -1,71 +0,0 @@
-.. _chapter-introduction:
-
-============
-Introduction
-============
-
-What is Ceres Solver?
----------------------
-Ceres is an industrial-grade C++ library for modeling and solving large and
-small nonlinear least squares problems of the form
-
-.. math:: \frac{1}{2}\sum_{i} \rho_i\left(\left\|f_i\left(x_{i_1}, ... ,x_{i_k}\right)\right\|^2\right).
-
-For a brief introduction to nonlinear solving in general, see the
-:ref:`chapter-tutorial`.
-
-Who uses Ceres Solver?
-----------------------
-
-* `Google Street View`_ panorama poses are computed with Ceres (`see video`_)
-* `Google Photo Tours`_ employ Ceres to pose all the photos
-* `Google Maps and Earth`_ imagery spatial alignment and satellite sensor calibration is done with Ceres
-* `Project Tango`_ uses Ceres as part of the SLAM pipeline
-* `Willow Garage's`_ SLAM pipeline uses Ceres for realtime bundle adjustment
-* `Android`_ uses Ceres for image processing and stitching, including for `Photo Sphere`_
-* `Blender's`_ `motion tracking module`_ depends critically on Ceres, using it
-  for 2D tracking, 3D reconstruction, panorama tracking, plane tracking, and
-  more; see the results in `Tears of Steel`_
-
-.. _Google Street View: http://www.google.com/maps/about/behind-the-scenes/streetview/
-.. _see video: https://www.youtube.com/watch?v=z00ORu4bU-A
-.. _Google Photo Tours: http://googlesystem.blogspot.com/2012/04/photo-tours-in-google-maps.html
-.. _Google Maps and Earth: http://www.google.com/earth/
-.. _Project Tango: https://www.google.com/atap/projecttango/
-.. _Willow Garage's: https://www.willowgarage.com/blog/2013/08/09/enabling-robots-see-better-through-improved-camera-calibration
-.. _Android: https://android.googlesource.com/platform/external/ceres-solver/
-.. _Photo Sphere: http://www.google.com/maps/about/contribute/photosphere/
-.. _Blender's: http://blender.org
-.. _motion tracking module: http://wiki.blender.org/index.php/Doc:2.6/Manual/Motion_Tracking
-.. _Tears of Steel: http://mango.blender.org/
-
-Why use Ceres Solver?
----------------------
-* Ceres has an **integrated modelling layer**, making it easy and intutive to
-  model large, complex cost functions with interacting terms, such as a moving
-  vehicle with multiple sensors and tricky dynamics.
-* Ceres has **integrated automatic differentiation**, avoiding the error-prone
-  task of manually computing derivatives.
-* Ceres can model a **wide variety of problems**, beyond simple nonlinear least
-  squares, thanks to robust loss functions and local parameterizations (e.g.
-  for quaternions).
-* Ceres is **very fast**, thanks to threaded cost function evaluators, threaded linear
-  solvers, and generous amounts of engineering time spent optimizing.
-* Ceres has **multiple nonlinear solvers** including trust region (fast, uses
-  more memory) and line search (slower, uses less memory).
-* Ceres has **multiple linear solvers** for both sparse and dense systems,
-  leveraging Eigen or MKL for dense solving, CHOLMOD or CXSparse for sparse
-  solving, and specialized linear solvers for bundle adjustment.
-* Ceres has **thorough automated tests** ensuring it is high-quality
-* Ceres is **industrial grade** thanks to **many compute-years** spent
-  running its code, analyzing the results, and improving it.
-* Ceres has **world-class solution quality**, with the best known results of
-  any least squares solver on the `NIST least squares precision benchmark`_.
-* Ceres has an **active community** encouraging contributions and mentoring
-  those starting out.
-* Ceres runs on **many platforms** including Linux, Windows, Mac OS X, Android, and
-  iOS (sort of).
-* Ceres is **liberally licensed (BSD)** so that you can use it freely in
-  commercial applications without releasing your code.
-
-.. _NIST least squares precision benchmark: https://groups.google.com/forum/#!topic/ceres-solver/UcicgMPgbXw
diff --git a/docs/source/tutorial.rst b/docs/source/tutorial.rst
index fdee1b8..7364d66 100644
--- a/docs/source/tutorial.rst
+++ b/docs/source/tutorial.rst
@@ -12,6 +12,19 @@
 .. math:: \frac{1}{2}\sum_{i} \rho_i\left(\left\|f_i\left(x_{i_1}, ... ,x_{i_k}\right)\right\|^2\right).
    :label: ceresproblem
 
+Problems of this form comes up in a broad range of areas across
+science and engineering - from `fitting curves`_ in statistics, to
+constructing `3D models from photographs`_ in computer vision.
+
+.. _fitting curves: http://en.wikipedia.org/wiki/Nonlinear_regression
+.. _3D model from photographs: http://en.wikipedia.org/wiki/Bundle_adjustment
+
+In this chapter we will learn how to solve :eq:`ceresproblem` using
+Ceres Solver. Full working code for all the examples described in this
+chapter and more can be found in the `examples
+<https://ceres-solver.googlesource.com/ceres-solver/+/master/examples/>`_
+directory.
+
 The expression
 :math:`\rho_i\left(\left\|f_i\left(x_{i_1},...,x_{i_k}\right)\right\|^2\right)`
 is known as a ``ResidualBlock``, where :math:`f_i(\cdot)` is a
@@ -33,12 +46,6 @@
 .. math:: \frac{1}{2}\sum_{i} \left\|f_i\left(x_{i_1}, ... ,x_{i_k}\right)\right\|^2.
    :label: ceresproblem2
 
-In this chapter we will learn how to solve :eq:`ceresproblem` using
-Ceres Solver. Full working code for all the examples described in this
-chapter and more can be found in the `examples
-<https://ceres-solver.googlesource.com/ceres-solver/+/master/examples/>`_
-directory.
-
 .. _section-hello-world:
 
 Hello World!